Academic literature on the topic 'Reward value'
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Journal articles on the topic "Reward value"
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Wang, Qi, Yan Sun, Ji Zhu, and Xiaohang Zhang. "The impact of uncertain rewards on customers’ recommendation intention in social networks." Internet Research 28, no. 4 (2018): 1029–54. http://dx.doi.org/10.1108/intr-03-2017-0116.
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Purpose The purpose of this paper is to research the effect of uncertain rewards on the recommendation intention in referral reward programs (RRPs) and investigate the interaction of tie strength and reward type on the recommendation intention. Design/methodology/approach The research adopts a quantitative exploratory approach through the use of experiments. Study 1 adopted a 2×2 between-participants design ((reward type: certain reward vs uncertain reward)×(tie strength: strong tie vs weak tie)). Respectively, by manipulating uncertain probabilities and expected value, Studies 2 and 3 further explore the effect of uncertain rewards and tie strength on customers’ referral intention. Findings This paper finds the following: compared to certain rewards, customers’ referral intention under uncertain rewards is higher and positive experience has a mediating effect between reward type and recommendation intention; when only the recommender is rewarded, the tie strength between the recommender and the receiver moderates the effect of reward type on the recommendation intention; for strong ties, customers’ recommendation intention is higher in uncertain reward condition, but for weak ties, customers’ willingness to recommend is almost the same in both reward types; when both the recommender and the receiver are rewarded, although certain rewards have a higher expected value than uncertain and random rewards, for strong ties, the participants have a higher referral intention under random rewards than that under uncertain rewards, which have a higher referral willingness than that under certain rewards. Additionally, for weak ties, the reverse is true. Originality/value The research has both theoretical implications for research on uncertain rewards and tie strength and practical implications for marketing managers designing and implementing RRPs.
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Pastor-Bernier, Alexandre, Arkadiusz Stasiak, and Wolfram Schultz. "Reward-specific satiety affects subjective value signals in orbitofrontal cortex during multicomponent economic choice." Proceedings of the National Academy of Sciences 118, no. 30 (2021): e2022650118. http://dx.doi.org/10.1073/pnas.2022650118.
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Sensitivity to satiety constitutes a basic requirement for neuronal coding of subjective reward value. Satiety from natural ongoing consumption affects reward functions in learning and approach behavior. More specifically, satiety reduces the subjective economic value of individual rewards during choice between options that typically contain multiple reward components. The unconfounded assessment of economic reward value requires tests at choice indifference between two options, which is difficult to achieve with sated rewards. By conceptualizing choices between options with multiple reward components (“bundles”), Revealed Preference Theory may offer a solution. Despite satiety, choices against an unaltered reference bundle may remain indifferent when the reduced value of a sated bundle reward is compensated by larger amounts of an unsated reward of the same bundle, and then the value loss of the sated reward is indicated by the amount of the added unsated reward. Here, we show psychophysically titrated choice indifference in monkeys between bundles of differently sated rewards. Neuronal chosen value signals in the orbitofrontal cortex (OFC) followed closely the subjective value change within recording periods of individual neurons. A neuronal classifier distinguishing the bundles and predicting choice substantiated the subjective value change. The choice between conventional single rewards confirmed the neuronal changes seen with two-reward bundles. Thus, reward-specific satiety reduces subjective reward value signals in OFC. With satiety being an important factor of subjective reward value, these results extend the notion of subjective economic reward value coding in OFC neurons.
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Gregorios-Pippas, Lucy, Philippe N. Tobler, and Wolfram Schultz. "Short-Term Temporal Discounting of Reward Value in Human Ventral Striatum." Journal of Neurophysiology 101, no. 3 (2009): 1507–23. http://dx.doi.org/10.1152/jn.90730.2008.
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Delayed rewards lose their value for economic decisions and constitute weaker reinforcers for learning. Temporal discounting of reward value already occurs within a few seconds in animals, which allows investigations of the underlying neurophysiological mechanisms. However, it is difficult to relate these mechanisms to human discounting behavior, which is usually studied over days and months and may engage different brain processes. Our study aimed to bridge the gap by using very short delays and measuring human functional magnetic resonance responses in one of the key reward centers of the brain, the ventral striatum. We used psychometric methods to assess subjective timing and valuation of monetary rewards with delays of 4.0–13.5 s. We demonstrated hyperbolic and exponential decreases of striatal responses to reward predicting stimuli within this time range, irrespective of changes in reward rate. Lower reward magnitudes induced steeper behavioral and striatal discounting. By contrast, striatal responses following the delivery of reward reflected the uncertainty in subjective timing associated with delayed rewards rather than value discounting. These data suggest that delays of a few seconds affect the neural processing of predicted reward value in the ventral striatum and engage the temporal sensitivity of reward responses. Comparisons with electrophysiological animal data suggest that ventral striatal reward discounting may involve dopaminergic and orbitofrontal inputs.
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Leathers, Marvin L., and Carl R. Olson. "In monkeys making value-based decisions, amygdala neurons are sensitive to cue value as distinct from cue salience." Journal of Neurophysiology 117, no. 4 (2017): 1499–511. http://dx.doi.org/10.1152/jn.00564.2016.
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Neurons in the lateral intraparietal (LIP) area of macaque monkey parietal cortex respond to cues predicting rewards and penalties of variable size in a manner that depends on the motivational salience of the predicted outcome (strong for both large reward and large penalty) rather than on its value (positive for large reward and negative for large penalty). This finding suggests that LIP mediates the capture of attention by salient events and does not encode value in the service of value-based decision making. It leaves open the question whether neurons elsewhere in the brain encode value in the identical task. To resolve this issue, we recorded neuronal activity in the amygdala in the context of the task employed in the LIP study. We found that responses to reward-predicting cues were similar between areas, with the majority of reward-sensitive neurons responding more strongly to cues that predicted large reward than to those that predicted small reward. Responses to penalty-predicting cues were, however, markedly different. In the amygdala, unlike LIP, few neurons were sensitive to penalty size, few penalty-sensitive neurons favored large over small penalty, and the dependence of firing rate on penalty size was negatively correlated with its dependence on reward size. These results indicate that amygdala neurons encoded cue value under circumstances in which LIP neurons exhibited sensitivity to motivational salience. However, the representation of negative value, as reflected in sensitivity to penalty size, was weaker than the representation of positive value, as reflected in sensitivity to reward size. NEW & NOTEWORTHY This is the first study to characterize amygdala neuronal responses to cues predicting rewards and penalties of variable size in monkeys making value-based choices. Manipulating reward and penalty size allowed distinguishing activity dependent on motivational salience from activity dependent on value. This approach revealed in a previous study that neurons of the lateral intraparietal (LIP) area encode motivational salience. Here, it reveals that amygdala neurons encode value. The results establish a sharp functional distinction between the two areas.
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Evans, Simon, Stephen M. Fleming, Raymond J. Dolan, and Bruno B. Averbeck. "Effects of Emotional Preferences on Value-based Decision-making Are Mediated by Mentalizing and Not Reward Networks." Journal of Cognitive Neuroscience 23, no. 9 (2011): 2197–210. http://dx.doi.org/10.1162/jocn.2010.21584.
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Real-world decision-making often involves social considerations. Consequently, the social value of stimuli can induce preferences in choice behavior. However, it is unknown how financial and social values are integrated in the brain. Here, we investigated how smiling and angry face stimuli interacted with financial reward feedback in a stochastically rewarded decision-making task. Subjects reliably preferred the smiling faces despite equivalent reward feedback, demonstrating a socially driven bias. We fit a Bayesian reinforcement learning model to factor the effects of financial rewards and emotion preferences in individual subjects, and regressed model predictions on the trial-by-trial fMRI signal. Activity in the subcallosal cingulate and the ventral striatum, both involved in reward learning, correlated with financial reward feedback, whereas the differential contribution of social value activated dorsal temporo-parietal junction and dorsal anterior cingulate cortex, previously proposed as components of a mentalizing network. We conclude that the impact of social stimuli on value-based decision processes is mediated by effects in brain regions partially separable from classical reward circuitry.
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Diao, Liuting, Wenping Li, Wenhao Chang, and Qingguo Ma. "Reward Modulates Unconsciously Triggered Adaptive Control Processes." i-Perception 13, no. 1 (2022): 204166952110738. http://dx.doi.org/10.1177/20416695211073819.
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Adaptive control (e.g., conflict adaptation) refers to dynamic adjustments of cognitive control processes in goal-directed behavior, which can be influenced by incentive rewards. Recently, accumulating evidence has shown that adaptive control processes can operate in the absence of conscious awareness, raising the question as to whether reward can affect unconsciously triggered adaptive control processes. Two experiments were conducted to address the question. In Experiment 1, participants performed a masked flanker-like priming task manipulated with high- and low-value performance-contingent rewards presented at the block level. In this experiment conflict awareness was manipulated by masking the conflict-inducing stimulus, and high- or low-value rewards were presented at the beginning of each block, and participants earned the reward contingent upon their responses in each trial. We observed a great conflict adaptation for high-value rewards in both conscious and unconscious conflict tasks, indicating reward-induced enhancements of consciously and unconsciously triggered adaptive control processes. Crucially, this effect still existed when controlling the stimulus-response repetitions in a rewarded masked Stroop-like priming task in Experiment 2. The results endorse the proposition that reward modulates unconsciously triggered adaptive control to conflict, suggesting that individuals may enable rewarding stimuli to dynamically regulate concurrent control processes based on previous conflict experience, regardless of whether the previous conflict was experienced consciously.
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Yamada, Hiroshi, Hitoshi Inokawa, Naoyuki Matsumoto, Yasumasa Ueda, Kazuki Enomoto, and Minoru Kimura. "Coding of the long-term value of multiple future rewards in the primate striatum." Journal of Neurophysiology 109, no. 4 (2013): 1140–51. http://dx.doi.org/10.1152/jn.00289.2012.
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Decisions maximizing benefits involve a tradeoff between the quantity of a reward and the cost of elapsed time until an animal receives it. The estimation of long-term reward values is critical to attain the most desirable outcomes over a certain period of time. Reinforcement learning theories have established algorithms to estimate the long-term reward values of multiple future rewards in which the values of future rewards are discounted as a function of how many steps of choices are necessary to achieve them. Here, we report that presumed striatal projection neurons represent the long-term values of multiple future rewards estimated by a standard reinforcement learning model while monkeys are engaged in a series of trial-and-error choices and adaptive decisions for multiple rewards. We found that the magnitude of activity of a subset of neurons was positively correlated with the long-term reward values, and that of another subset of neurons was negatively correlated throughout the entire decision-making process in individual trials: from the start of the task trial, estimation of the values and their comparison among alternatives, choice execution, and evaluation of the received rewards. An idiosyncratic finding was that neurons showing negative correlations represented reward values in the near future (high discounting), while neurons showing positive correlations represented reward values not only in the near future, but also in the far future (low discounting). These findings provide a new insight that long-term value signals are embedded in two subsets of striatal neurons as high and low discounting of multiple future rewards.
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Rigley, Eryn, Adriane Chapman, Christine Evers, and Will McNeill. "ME: Modelling Ethical Values for Value Alignment." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 26 (2025): 27608–16. https://doi.org/10.1609/aaai.v39i26.34974.
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Value alignment, at the intersection of moral philosophy and AI safety, is dedicated to ensuring that artificially intelligent (AI) systems align with a certain set of values. One challenge facing value alignment researchers is accurately translating these values into a machine readable format. In the case of reinforcement learning (RL), a popular method within value alignment, this requires designing a reward function which accurately defines the value of all state-action pairs. It is common for programmers to hand-set and manually tune these values. In this paper, we examine the challenges of hand-programming values into reward functions for value alignment, and propose mathematical models as an alternative grounding for reward function design in ethical scenarios. Experimental results demonstrate that our modelled-ethics approach offers a more consistent alternative and outperforms our hand-programmed reward functions.
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Ostaszewski, Pawel, and Katarzyna Karzel. "Discounting of Delayed and Probabilistic Losses of Different Amounts." European Psychologist 7, no. 4 (2002): 295–301. http://dx.doi.org/10.1027//1016-9040.7.4.295.
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Previous research has shown that the value of a larger future reward is discounted less steeply than the value of a smaller future reward. The value of probabilistic reward has been shown to have either an opposite effect on discounting (when a smaller reward is not certain its value was discounted less steeply than the value of a larger reward) or no effect on the rate of discounting at all. The present article shows the results for delayed and probabilistic losses: The same hyperbola-like functions describe temporal and probabilistic discounting of both rewards and losses. In the case of losses, larger delayed amounts are discounted less steeply than smaller delayed amounts (as in the case of delayed rewards). No relationship was found between the amount of probabilistic losses and the rate of discounting of their value. In summary, the results show that the description of the discounting process and the effect of amount on the rate of discounting are basically the same in case of both rewards and losses.
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Ichikawa, Yoshihiro, and Keiki Takadama. "Designing Internal Reward of Reinforcement Learning Agents in Multi-Step Dilemma Problem." Journal of Advanced Computational Intelligence and Intelligent Informatics 17, no. 6 (2013): 926–31. http://dx.doi.org/10.20965/jaciii.2013.p0926.
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This paper proposes the reinforcement learning agent that estimates internal rewards using external rewards in order to avoid conflict in multi-step dilemma problem. Intensive simulation results have revealed that the agent succeeds in avoiding local convergence and obtains a behavior policy for reaching a higher reward by updating the Q-value using the value that is subtracted the average reward from an external reward.
Dissertations / Theses on the topic "Reward value"
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Galtress, Tiffany. "Mechanisms of reward value, timing and choice." Thesis, University of York, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.444672.
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Williams, Elin. "Examining the social reward value of biological motion." Thesis, Bangor University, 2018. https://research.bangor.ac.uk/portal/en/theses/examining-the-social-reward-value-of-biological-motion(8a8e65c0-e9bf-4626-b465-74b31e9641b6).html.
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As humans, we share a strong desire to interact with other people. This strong motivation to engage socially directs our attention to social signals, guides us to participate in behaviours that help us to establish, maintain, and enhance our relationships with others, and allows us to enjoy social interactions and to find them rewarding. However, the Social Motivation Theory posits that individuals with Autism Spectrum Disorder may have deficits in social motivation, which may lead to difficulties in social interactions and communication. This thesis employs several methods (including behavioural, psychophysiological and neurological) to investigate social motivation in the typical population, and examines how autistic traits influence the reward value assigned to social stimuli. Specifically, this thesis investigates social motivation in relation to an important type of social stimulus, namely biological motion, which has not been the topic of research investigating social motivation. The first empirical chapter (Chapter 3) presents a behavioural experiment that investigates the reward value of biological motion, and how this value changes as a function of autistic traits among the participant sample. The following chapter (Chapter 4) comprises two eye-tracking experiments aiming to address how viewing biological motion affects attention and arousal. The final empirical chapter (Chapter 5) employs functional magnetic resonance imaging (fMRI) to examine brain regions involved in the anticipation of social reward or social punishment in a task where participants work to either receive positive feedback or avoid negative feedback. As a whole, this thesis sheds valuable new light on questions surrounding social motivation, such as whether individuals find a broad conceptualisation of social stimuli rewarding and whether the perceived reward value of social stimuli is influenced by autistic traits. The findings from this work have important implications for developing a greater understanding of social motivation and human social behaviour more broadly.
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Smith, Aaron Paul. "NEUROBEHAVIORAL MEASUREMENTS OF NATURAL AND OPIOID REWARD VALUE." UKnowledge, 2019. https://uknowledge.uky.edu/psychology_etds/164.
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In the last decade, (non)prescription opioid abuse, opioid use disorder (OUD) diagnoses, and opioid-related overdoses have risen and represent a significant public health concern. One method of understanding OUD is as a disorder of choice that requires choosing opioid rewards at the expense of other nondrug rewards. The characterization of OUD as a disorder of choice is important as it implicates decision- making processes as therapeutic targets, such as the valuation of opioid rewards. However, reward-value measurement and interpretation are traditionally different in substance abuse research compared to related fields such as economics, animal behavior, and neuroeconomics and may be less effective for understanding how opioid rewards are valued. The present research therefore used choice procedures in line with behavioral/neuroeconomic studies to determine if drug-associated decision making could be predicted from economic choice theories. In Experiment 1, rats completed an isomorphic food-food probabilistic choice task with dynamic, unpredictable changes in reward probability that required constant updating of reward values. After initial training, the reward magnitude of one choice subsequently increased from one to two to three pellets. Additionally, rats were split between the Signaled and Unsignaled groups to understand how cues modulate reward value. After each choice, the Unsignaled group received distinct choice-dependent cues that were uninformative of the choice outcome. The Signaled group also received uninformative cues on one option, but the alternative choice produced reward-predictive cues that informed the trial outcome as a win or loss. Choice data were analyzed at a molar level using matching equations and molecular level using reinforcement learning (RL) models to determine how probability, reward magnitude, and reward-associated cues affected choice. Experiment 2 used an allomorphic drug versus food procedure where the food reward for one option was replaced by a self-administered remifentanil (REMI) infusion at doses of 1, 3 and 10 μg/kg. Finally, Experiment 3 assessed the potential for both REMI and food reward value to be commonly scaled within the brain by examining changes in nucleus accumbens (NAc) Oxygen (O2) dynamics. Results showed that increasing reward probability, magnitude, and the presence of reward-associated cues all independently increased the propensity of choosing the associated choice alternative, including REMI drug choices. Additionally, both molar matching and molecular RL models successfully parameterized rats’ decision dynamics. O2 dynamics were generally commensurate with the idea of a common value signal for REMI and food with changes in O2 signaling scaling with the reward magnitude of REMI rewards. Finally, RL model-derived reward prediction errors significantly correlated with peak O2 activity for reward delivery, suggesting a possible neurological mechanism of value updating. Results are discussed in terms of their implications for current conceptualizations of substance use disorders including a potential need to change the discourse surrounding how substance use disorders are modeled experimentally. Overall, the present research provides evidence that a choice model of substance use disorders may be a viable alternative to the disease model and could facilitate future treatment options centered around economic principles.
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Fiallos, Ana Marcia. "Brain circuits for the representation of subjective reward value." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/62716.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, February 2011.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 97-102).<br>Successful interaction with the external world requires choosing appropriate actions in the context of available choices. Such decisions require the evaluation of the reward magnitude, or value, associated with each potential action. Delineating the neural circuits involved in this process remains an important goal in systems neuroscience. However, little is known about the neural circuits that compute, or represent, low level primary reward signals. We have combined quantitative psychophysical measures of subjective reward magnitude elicited by rewarding electrical brain stimulation, fMRI as a readout of whole-brain neural activity, and local inactivation of brain structures, to identify the neural representation of subjective reward magnitude. We find that multiple brain regions are activated by rewarding brain stimulation, but only two brain regions, the nucleus accumbens and the central and basolateral nucleus of the amygdala, exhibit patterns of activity levels that track the reward magnitude measured psychophysically, suggesting a role in the neural representation of reward magnitude. Furthermore, pharmacological silencing of the ventral tegmental area (VTA) disrupts reward-tracking behavior and increases stimulus-dependent activity in the nucleus accumbens and amygdala. Together these data suggest that ascending and descending pathways combine to produce a signal that ultimately guides behavior and is subject to modulation by VTA inputs.<br>by Ana Marcia Fiallos.<br>Ph.D.
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James, Michael. "The estimation of reward and value in reinforcement learning." Thesis, University of York, 2003. http://etheses.whiterose.ac.uk/14066/.
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Roper, Zachary Joseph Jackson. "The manifold role of reward value on visual attention." Diss., University of Iowa, 2015. https://ir.uiowa.edu/etd/2005.
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The environment is abundant with visual information. Each moment, this information competes for representation in the brain. From billboards and pop-up ads to smart phones and flat screens, in modern society our attention is constantly drawn from one salient object to the next. Learning how to focus on the objects that are most important for the current task is a major developmental hurdle. Fortunately, rewards help us to learn what is important by providing feedback signals to the brain. Sometimes, in adolescence for example, reward seeking can become the pre-potent response. This can ultimately lead to risky and impulsive behaviors that have devastating consequences. Until recently, little has been known about how rewards operate to influence the focus of attention.
In this document, I first demonstrate the robustness of various behavioral paradigms designed to measure reward processing in vision. I found that even mundane rewards, such as images of money, are effective enough to prime the attentional system on the basis of value. Remarkably, this effect extended to images of Monopoly money. This observation suggests that whole classes of visual stimuli, such as food, pornography, commercial logos, corporate brands, or money, each with its own reward salience value, are likely vying for representation in the brain. This work has implications for the growing digital economy as it suggests that novel value systems, such as the digital currency Bitcoin, could eventually become as psychologically relevant as physical currency provided sufficient use and exposure. Likewise, this work has implications for gamification in the industrial setting.
Next, I examined the sensitivity of the system to make optimal economic decisions. When faced with an economic choice normative theories of decision-making suggest that the economic actor will choose the response that affords the greatest expected utility. Contrary to this account, I developed a new behavioral paradigm (reward contingent capture) and reveal that the attentional homunculus is a fuzzy mathematician. Specifically, I found that low-level attentional processes conform to the same probability distortions observed in prospect theory. This finding supports a unified value learning mechanism across several domains of cognition and converges with evidence from monkey models.
Then, I demonstrate the influence of rewards on high-order search parameters. I found that images of money can implicitly encourage observers to preferentially adopt one of two search strategies – one that values salience versus one that values goals. Together, my results expose two distinct ways in which the very same rewards can affect attentional behavior – by tuning the salience of specific features and by shaping global search mode settings.
Lastly, I draw from my empirical results to present a unified model of the manifold role of rewards on visual attention. This model makes clear predictions for clinical applications of rewarded attention paradigms because it incorporates a dimension of complexity upon which learning processes can operate on attention. Thus, future work should acknowledge how individual traits such as developmental trajectory, impulsivity, and risk-seeking factors differentially interact with low- and high-level attentional processes.
In sum, this document puts forward the notion that rewards serve a compelling role in visual awareness. The key point however is not that rewards can have an effect on attention but that due to the nature of visual processing, reward signals are likely always tuning attention. In this way we can consider reward salience an attentional currency. This means then that deciding where to attend is a matter of gains and losses.
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Smedley, Lisa. "Customer Perceived Value of Credit Card Rewards : A study on Canadian Consumers." Thesis, Högskolan i Gävle, Akademin för utbildning och ekonomi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-13865.
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Abstract Title: Customer Perceived Value of Credit Card Rewards - A study on Canadian Consumers Level: Final assignment for Bachelor’s Degree in Business Administration Author: Lisa Smedley Supervisor: Jonas Kågström Date: 2013 - January Aim: The aim of this study is to investigate what influences Customer Perceived Value; where Canadian consumers’ preferences lie in terms of rewards in the Canadian credit card industry. Method: After researching previous studies and determining what constructs have been utilized prior on similar research topics, I implement a quantitative, and to some extend iterative, research approach. Through survey research, I investigate Canadian consumer preferences through a survey sample of 124 Canadian consumers in Calgary, Alberta, Canada. Result & Conclusions: One finding in the study indicates that utilitarian benefits, which provide financial gain for the card holder, are perceived by respondents as the most valuable reward. Another finding is that inexperienced credit card holders see significantly greater value in symbolic benefits than experienced card holders do. The present study does not support the theory that customer involvement influences the customer’s perception of rewards. 2 Suggestions for future research: More extensive research is needed on the subject of whether Canadian consumers’ perceived value of rewards is influenced by their level of involvement in their credit card. Also, studies involving additional factors that could possibly determine a consumer’s perception of rewards, such as income and ethnicity should be investigated for a more well-rounded understanding of customer preferences. Contribution of the thesis: The present study contributes with new findings that can be of substantial significance for Canadian financial institutions as it provides insight into what credit card rewards Canadian consumers perceive as being valuable to them. Key words: Rewards programs, credit cards, customer loyalty, perceived customer value, timing of reward, type of reward, dimension of benefit, utilitarian, hedonic, symbolic
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Mattson, Karla M. "The value of signals for reward: Choice in concurrent chains." Thesis, University of Canterbury. Psychology, 2005. http://hdl.handle.net/10092/4642.
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A number of studies indicate that a signalling effect occurs when stimuli are presented during the terminal link of a concurrent-chains procedure, which signal whether or not probabilistic reinforcement is forthcoming at the end of the trial. The effect of these signals is a reduced preference for the richer alternative. This thesis includes five experiments aimed to investigate this. The overall purpose of this research is to investigate the effect on preference of differential signalling of reinforcement that differs in terms of the variable being signalled. Furthermore, these experiments are aimed at investigating the manner in which signalling affects preference when multiple dimensions of reinforcement are varied in a signalling procedure. Asking the question how does signalling affect sensitivity to various dimensions of reinforcement and how does this change when more than one dimension is varied?
The first experiment involved a simple replication of previous work with percentage-reinforcement procedures. It further extends that work by signalling the size of the reinforcer rather than its probability. Pigeons were given the choice between two alternatives with identical-duration initial and terminal links. Choice of one alternative (uncertain) led to one of two possible signalled outcomes, reinforcement (3.5 s) or blackout, with a probability of .5. Choice of the other alternative (certain) always resulted in food (3.5 s) at the end of the delay. When the scheduled outcome on the uncertain alternative was differentially signalled, there was a moderate preference for the certain side. Moreover, when the scheduled outcome on the uncertain side was not differentially signalled, preference for the certain side became more extreme. This result replicates the signalling effect. With a similar design, another three conditions manipulated the magnitude of primary reinforcement, rather than its probability. When primary reinforcement was arranged like this, a weaker signalling effect was obtained.
Two further experiments investigated the effect of signals on preference for alternatives that differed in either relative variability or expected magnitude of reinforcement, while the other variable was held constant. In Experiment 2, pigeons were offered the choice between two alternatives that differed in relative variability of reinforcement. Each alternative delivered one of two possible reinforcer magnitudes at the end of a terminal link: these magnitudes were either the same (fixed) or were different (mixed). In some conditions, terminal-link outcomes were signalled and in others they were not. Results showed that pigeons preferred fixed over signalled mixed magnitudes of reinforcement, and signalled mixed over unsignalled mixed magnitudes of reinforcement. Thus, these alternatives could be ordered in terms of preference: fixed, signalled mixed and unsignalled mixed. Finally, signalling does indeed moderate the preference for fixed over mixed magnitudes.
In the third experiment, pigeons completed a two-component signalled concurrent-chains procedure in which the relative expected magnitude varied across alternatives as all other dimensions of reinforcement were held constant. Therefore, this experiment investigated the effects of signalling on preference between alternatives differing in relative expected magnitude of reinforcement. A slight signalling effect was obtained, with slightly reduced preference in the signalled relative to the unsignalled condition. Overall, these two experiments confirm that signalling acts on the preference for fixed magnitudes of reinforcement and to a lesser extent, preference for the larger of two expected magnitudes of reinforcement.
The final two experiments investigated the effect of signals on preference in a procedure that varied parametrically either relative probability and immediacy of reinforcement, or probability and magnitude of reinforcement. The effects of relative reinforcer immediacy or magnitude and probability on choice in concurrent chains were examined, under conditions in which terminal-link outcomes (reinforcement or extinction) were either signalled or unsignalled. Pigeons responded in a three-component concurrent-chains procedure with either independent or interdependent initial links. The percentage of reinforcement was varied across conditions, while the immediacy or magnitude of reinforcement was varied across components. Both signalled and unsignalled conditions were arranged. Generalised-matching analyses revealed a strong signalling effect: sensitivity to relative reinforcer probability was greater in the unsignalled compared to signalled conditions. However, sensitivities to relative immediacy and magnitude were also greater in the unsignalled conditions. Overall, the data suggest that signalling reinforcement and extinction outcomes may attenuate sensitivity to all terminal-link variables, not just reinforcer probability.
These experiments have investigated the signalling effect using a variety of methods. They have contributed several replications of the effect, and added valuable information regarding the effects on preference of signalling reinforcement outcomes. The most impressive finding of this research is that signalling has a global effect on sensitivity to all dimensions of reinforcement and that models of conditioned reinforcement are best suited to analyse these results.
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Skog, Emil. "The value of intrinsic motivation in relation to primary reward." Thesis, Umeå universitet, Institutionen för psykologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-136827.
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Intrinsically motivated behaviors have been defined as behaviors that do not come with any primary external rewards. Previous studies on intrinsic motivation has often depended on self-report measures, or only tested how subjects’ motivation is impacted by punishments or no gain differences. The present study aims to test these two conditions, with the addition of a third, where selecting an information gain option results in reward. This will be tested empirically using an existing information theoretic operationalization, where subjects will choose between information gain or no information gain. Results of the study show that information gain has some degree of attraction when subjects expect no gain differences, and when comparing punishment and reward conditions.<br>Curiosity and the reward of learning
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Tsoulfas, Georgios. "Temporal discounting of expected value of reward in the medial intraparietal cortex." Thesis, McGill University, 2011. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=103657.
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Previous work has shown that expected value of reward associated with a reach modulates neurons in the medial intraparietal cortex (MIP) and that this reward signal can be decoded. In this study, we investigated the reliability of reward coding in MIP by examining how given reward magnitudes are encoded when presented in different contexts. We are interested in determining how prior knowledge of reward is used to interpret information about the reward in the current trial. We recorded from single neurons in MIP while two rhesus macaque monkeys performed a memory reach task under two conditions. In the first condition, high and low reward values were randomly interleaved trial by trial (variable reward schedule), while in the second condition only one of these reward values was delivered for a block of trials (constant reward schedule). For both reward schedules, the reward magnitude was indicated by a cue preceding the delay period of each trial. Each recording session consisted of a variable reward schedule as well as a small and large constant reward schedule. For the same reward, the firing rate of neurons in the delay period changed significantly between the constant and variable reward schedule conditions. A model that discounts past acquired rewards and formulates a weighted history of reward for the present trial is proposed to explain the observed differences in firing rate between contexts. We identify neurons that fire in accordance to a temporal discount of reward, with significant correlation (R2 > 0.25) between the model and experimental data, suggesting that the neuronal activation within MIP is modulated both by current expected value of reward and discounted past reward magnitudes.<br>De précédents travaux ont démontré que l'espérance face à la valeur de la récompense associée à une tâche d'atteinte, affecte l'activité des neurones du cortex intraparietal médial (MIP) et que ce signal de récompense peut-être décodé. Dans cette étude, nous nous attaquons à la fiabilité de l'encodage de la récompense dans la région MIP en examinant comment la quantification de la récompense est encodée quand elle est présentée dans différents contextes. Nous sommes intéressés à savoir si la connaissance acquise au cours des essais précédents est utilisée pour interpréter l'information a propos de la récompense de l'essai courant. Nous avons échantillonné l'activité de neurones, un à un, alors que deux singes, macaque rhésus, performaient une tâche d'atteinte avec délai, sous deux conditions de remise de récompense. Soumis à première condition, les grandes et petites quantités de récompense ont été enchainées de façon aléatoire (ordonnancement de récompense aléatoire), alors que sous la deuxième condition un seul format de récompense a été maintenu pour toute la durée du bloc d'essais (ordonnancement de récompense constant). Pour les deux types d'ordonnancement, la quantité de récompense était indiquée par un signal précédent la période de délai de chaque essai. Chaque séance d'enregistrement comprend un bloc d'ordonnancement aléatoire, un bloc de grandes récompenses constantes et un bloc de petites récompenses constantes. Pour la même récompense, le taux de mise à feu des neurones dans la période de délai ont été affecté de façon significative par l'ordonnancement des récompenses. Un modèle est proposé pour expliquer la différence dans les taux de mises à feu. Nous identifions les neurones qui font feu en accord avec une réduction temporelle de la récompense, avec une corrélation significative (R2 > 0.25) entre le model et les données expérimentales, suggérant que l'activité neuronale dans MIP est fonction à la fois de l'espérance de la valeur de la récompense présente et de la réduction temporelle des récompenses passées.
Books on the topic "Reward value"
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1960-, Brown Duncan, ed. Strategic reward: How organizations add value through reward. Kogan Page, 2006.
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Morillo, Carolyn R. Contingent creatures: A reward event theory of motivation and value. Littlefield Adams Books, 1995.
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Kershnar, Stephen. Desert and virtue: A theory of intrinsic value. Lexington Books, 2010.
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Alain, Mitrani, Dalziel Murray M, and Fitt David, eds. Competency based human resource management: Value-driven strategies for recruitment, development and reward. Kogan Page, 1992.
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Consultants, Hay-MSL Management, ed. Equal pay for work of equal value: A code of practice for personnel E.R. and reward professionals. Hay-MSL, 1985.
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Egginton, Don. Directors' perceptions of the effects and values of share option rewards. University of Bristol, Department of Economics, 1994.
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Kennedy, James J. Line officers' views on stated USDA Forest Service values and the agency reward system. U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2005.
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L, Emerton, ed. Values and rewards: Counting and capturing ecosystem water services for sustainable development. IUCN, 2005.
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O’Brien, Justin, and Sheena Karangi. Customer Lifetime Value Analysis: Designing a Multi-Company Rewards Programme to Incentivise Beneficial Customer Behaviors. Edited by Brian A. Vander Schee. SAGE Publications, Inc., 2024. http://dx.doi.org/10.4135/9781071959220.
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Strategic Reward: How Organizations Add Value Through Reward. Kogan Page, Limited, 2010.
Find full textBook chapters on the topic "Reward value"
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Felderer, Michael, Wilhelm Hasselbring, Heiko Koziolek, et al. "Ernst Denert Software Engineering Awards 2019." In Ernst Denert Award for Software Engineering 2019. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58617-1_1.
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AbstractThe need to improve software engineering practices is continuously rising and software development practitioners are highly interested in improving their software systems and the methods to build them. And well, software engineering research has numerous success stories. The Ernst Denert Software Engineering Award specifically rewards researchers that value the practical impact of their work and aim to improve current software engineering practices. This chapter summarizes the awards history as well as the current reward process and criteria.
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Bork, Alexander, Joost-Pieter Katoen, and Tim Quatmann. "Under-Approximating Expected Total Rewards in POMDPs." In Tools and Algorithms for the Construction and Analysis of Systems. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99527-0_2.
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AbstractWe consider the problem: is the optimal expected total reward to reach a goal state in a partially observable Markov decision process (POMDP) below a given threshold? We tackle this—generally undecidable—problem by computing under-approximations on these total expected rewards. This is done by abstracting finite unfoldings of the infinite belief MDP of the POMDP. The key issue is to find a suitable under-approximation of the value function. We provide two techniques: a simple (cut-off) technique that uses a good policy on the POMDP, and a more advanced technique (belief clipping) that uses minimal shifts of probabilities between beliefs. We use mixed-integer linear programming (MILP) to find such minimal probability shifts and experimentally show that our techniques scale quite well while providing tight lower bounds on the expected total reward.
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Ashok, Pranav, Krishnendu Chatterjee, Przemysław Daca, Jan Křetínský, and Tobias Meggendorfer. "Value Iteration for Long-Run Average Reward in Markov Decision Processes." In Computer Aided Verification. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63387-9_10.
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Harris, Trevor S., Juliet Estridge, and Doron Nissim. "Morgan Stanley ModelWare's Approach to Intrinsic Value: Focusing on Risk-Reward Trade-offs." In Equity Valuation. John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119208754.part4.
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Castro, Pablo F., Pedro R. D’Argenio, Ramiro Demasi, and Luciano Putruele. "Playing Against Fair Adversaries in Stochastic Games with Total Rewards." In Computer Aided Verification. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13188-2_3.
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AbstractWe investigate zero-sum turn-based two-player stochastic games in which the objective of one player is to maximize the amount of rewards obtained during a play, while the other aims at minimizing it. We focus on games in which the minimizer plays in a fair way. We believe that these kinds of games enjoy interesting applications in software verification, where the maximizer plays the role of a system intending to maximize the number of “milestones” achieved, and the minimizer represents the behavior of some uncooperative but yet fair environment. Normally, to study total reward properties, games are requested to be stopping (i.e., they reach a terminal state with probability 1). We relax the property to request that the game is stopping only under a fair minimizing player. We prove that these games are determined, i.e., each state of the game has a value defined. Furthermore, we show that both players have memoryless and deterministic optimal strategies, and the game value can be computed by approximating the greatest-fixed point of a set of functional equations. We implemented our approach in a prototype tool, and evaluated it on an illustrating example and an Unmanned Aerial Vehicle case study.
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Gutsche, Linda, and Loïs Vanhée. "The Value of Knowledge: Joining Reward and Epistemic Certainty Optimisation for Anxiety-Sensitive Planning." In Autonomous Agents and Multiagent Systems. Best and Visionary Papers. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56255-6_2.
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Alfaro, Emigdio. "Urgent!…To Reward Innovation in Information Technologies with a Real Focus on Value Generation." In Revolution of Innovation Management. Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-137-57475-6_6.
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Bissonette, Gregory B., and Matthew R. Roesch. "Neurophysiology of Reward-Guided Behavior: Correlates Related to Predictions, Value, Motivation, Errors, Attention, and Action." In Behavioral Neuroscience of Motivation. Springer International Publishing, 2015. http://dx.doi.org/10.1007/7854_2015_382.
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Kesner, Raymond P., and Paul E. Gilbert. "Process-oriented view of amygdala and hippocampus: Mediation of reward value and spatial location information." In Memory consolidation: Essays in honor of James L. McGaugh. American Psychological Association, 2001. http://dx.doi.org/10.1037/10413-013.
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Falcone, Rossella, Mariko McDougall, David Weintraub, Tsuyoshi Setogawa, and Barry Richmond. "Neural Coding of Reward Value in Richly Modulated Spike Patterns in Monkey Ventrolateral Prefrontal Cortex." In Advances in Cognitive Neurodynamics (VII). Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0317-4_33.
Full textConference papers on the topic "Reward value"
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Mao, Xin, Feng-Lin Li, Huimin Xu, Wei Zhang, Wang Chen, and Anh Tuan Luu. "Don’t Forget Your Reward Values: Language Model Alignment via Value-based Calibration." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.976.
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He, Tianyu, Dongye Zhuang, and Haibin Xie. "Robust Belief-Reward Approximate Value Iteration for Dynamic Detection Systems Allocation in Uncertain Counter-Drone Operations*." In 2024 China Automation Congress (CAC). IEEE, 2024. https://doi.org/10.1109/cac63892.2024.10865056.
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Divan, Brooke A., Rebekah Wilson, and Miranda Etchison. "Small Expense, Big Reward - the Impact and Value of Quality Assurance Testing of Coatings for Hydraulic Steel Structures." In SSPC 2016 Greencoat. SSPC, 2016. https://doi.org/10.5006/s2016-00017.
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Abstract Quality Assurance (QA) paint testing is an important obligation of any paint manufacturer and/or end user. Each year, hundreds of batches slotted to be applied on US Army Corps of Engineers (USACE) hydraulic steel structures around the country are submitted to be tested at the Engineering Research Development Center, Construction Engineering Research Laboratory, Paint Technology Center (ERDC-CERL-PTC). A significant fraction of those samples fail. The most common samples supplied by numerous manufacturers include solvents, vinyls, coal tar epoxies, polyurethanes, and military specified epoxy polyamides. Last year, out of the 200 samples tested by the PTC, more than 25% failed to meet their associated specification. The cost and time of quality assurance (QA) testing is negligible compared to the expense of a large scale coating failure on a hydraulic steel structure in the field. Failures are monitored on small scale coupons in the laboratory through tests such as impact, adhesion, compositional analyses, application properties, and overall performance in multiple service environments. This proactive solution serves as an insurance policy that failures will not occur on a larger scale. This crucial testing step is an inexpensive fail-safe method to ensure that coatings will perform as expected on steel structures around the nation. The small upfront time and financial investment can save millions of dollars by minimizing coating maintenance, repainting projects, and the huge expense of corrosion. Subpar results help to inform manufacturers and end users of concerns products to help to determine what is askew in the coating and provide insight on how to remediate it.
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Tian, Yuhe, Ayooluwa Akintola, Yazhou Jiang, et al. "Reinforcement Learning-Driven Process Design: A Hydrodealkylation Example." In Foundations of Computer-Aided Process Design. PSE Press, 2024. http://dx.doi.org/10.69997/sct.119603.
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In this work, we present a follow-up work of reinforcement learning (RL)-driven process design using the Institute for Design of Advanced Energy Systems Process Systems Engineering (IDAES-PSE) Framework. Herein, process designs are generated as stream inlet-outlet matrices and optimized using the IDAES platform, the objective function value of which is the reward to RL agent. Deep Q-Network is employed as the RL agent including a series of convolutional neural network layers and fully connected layers to compute the actions of adding or removing any stream connections, thus creating a new process design. The process design is then informed back to the RL agent to refine its learning. The iteration continues until the maximum number of steps is reached with feasible process designs generated. To further expedite the RL search of the design space which can comprise the selection of any candidate unit(s) with arbitrary stream connections, we investigate the role of RL reward function and their impacts on exploring more complicated versus intensified process configurations. A sub-space search strategy is also developed to branch the combinatorial design space to accelerate the discovery of feasible process design solutions particularly when a large pool of candidate process units is selected by the user. The potential of the enhanced RL-assisted process design strategy is showcased via a hydrodealkylation example.
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Acosta-Pavas, Juan Camilo, David Camilo Corrales, Susana Mar�a Alonso Villela, et al. "Learning-based Control Approach for Nanobody-scorpion Antivenom Optimization." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.149893.
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One market scope of bioindustries is the production of recombinant proteins for its application in serotherapy. However, its process's monitoring and optimization present limitations. There are different approaches to optimize bioprocess performance; one is using model-based control strategies such as Model Predictive Control (MPC). Another strategy is learning-based control, such as Reinforcement Learning (RL). In this work, an RL approach was applied to maximize the production of recombinant proteins in E. coli at the�induction phase using as a control variable the substrate feed flow rate (Fin). The RL model was trained using the actor-critic Twin-Delayed Deep Deterministic (TD3) Policy Gradient agent. The reward corresponded to the maximum value of protein productivity. The environment was represented with a dynamic hybrid model. The optimization was evaluated by stages of two hours to check the protein productivity performance. Afterwards, the results were compared with an MPC approach. Finally, the control approaches were trained considering temperature disturbances. The results elucidate that the RL approach could be implemented as a control strategy, reaching values from 0.014 mg/h to 0.079 mg/h through all the optimization stages previously demonstrated to be the optimal ones. Despite exhibiting temperature disturbances, the RL approach demonstrated its robustness by adapting the control action to maintain similar protein productivity values.
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Fultz, Benjamin S. "True Value of Quality: a Case History of a Success Story." In Paint and Coatings Expo (PACE) 2006. SSPC, 2006. https://doi.org/10.5006/s2006-00027.
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Abstract A case study of how poor initial quality control resulted in a complete coatings rework of the underwater bottom (exterior hull) of a large Floating Storage Unit (FSU) and how a good quality control program, during rework, resulted in the documented long term performance of the second application underwater hull coating system.
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Luo, Yudong, Oliver Schulte, and Pascal Poupart. "Inverse Reinforcement Learning for Team Sports: Valuing Actions and Players." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/464.
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A major task of sports analytics is to rank players based on the impact of their actions. Recent methods have applied reinforcement learning (RL) to assess the value of actions from a learned action value or Q-function. A fundamental challenge for estimating action values is that explicit reward signals (goals) are very sparse in many team sports, such as ice hockey and soccer. This paper combines Q-function learning with inverse reinforcement learning (IRL) to provide a novel player ranking method. We treat professional play as expert demonstrations for learning an implicit reward function. Our method alternates single-agent IRL to learn a reward function for multiple agents; we provide a theoretical justification for this procedure. Knowledge transfer is used to combine learned rewards and observed rewards from goals. Empirical evaluation, based on 4.5M play-by-play events in the National Hockey League (NHL), indicates that player ranking using the learned rewards achieves high correlations with standard success measures and temporal consistency throughout a season.
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Hanna, Hosam, Jin Yao, and Khaldoun Zreik. "Approximation of Expected Reward Value in MMDP." In Communication Technologies: from Theory to Applications (ICTTA). IEEE, 2008. http://dx.doi.org/10.1109/ictta.2008.4530314.
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Chen, Xinning, Xuan Liu, Yanwen Ba, Shigeng Zhang, Bo Ding, and Kenli Li. "Selective Learning for Sample-Efficient Training in Multi-Agent Sparse Reward Tasks (Extended Abstract)." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/927.
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Learning effective strategies in sparse reward tasks is one of the fundamental challenges in reinforcement learning. This becomes extremely difficult in multi-agent environments, as the concurrent learning of multiple agents induces the non-stationarity problem and a sharply increased joint state space. Existing works have attempted to promote multi-agent cooperation through experience sharing. However, learning from a large collection of shared experiences is inefficient as there are only a few high-value states in sparse reward tasks, which may instead lead to the curse of dimensionality in large-scale multi-agent systems. This paper focuses on sparse-reward multi-agent cooperative tasks and proposes an effective experience-sharing method, Multi-Agent Selective Learning (MASL), to boost sample-efficient training by reusing valuable experiences from other agents. MASL adopts a retrogression-based selection method to identify high-value traces of agents from the team rewards, based on which some recall traces are generated and shared among agents to motivate effective exploration. Moreover, MASL selectively considers information from other agents to cope with the non-stationarity issue while enabling efficient training for large-scale agents. Experimental results show that MASL significantly improves sample efficiency compared with state-of-the-art MARL algorithms in cooperative tasks with sparse rewards.
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Okatan, M., R. Komorowski, and H. B. Eichenbaum. "Reward-predictive value in learning-related hippocampal neural activity." In 2009 IEEE 35th Annual Northeast Bioengineering Conference. IEEE, 2009. http://dx.doi.org/10.1109/nebc.2009.4967723.
Full textReports on the topic "Reward value"
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Alfaro, Emigdio. Urgent! ... To reward the innovation on information technologies, with a real focus on the value generation. CENTRUM Catolica Graduate Business School, 2015. http://dx.doi.org/10.7835/ccwp-2015-11-0025.
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Andrabi, Tahir, Natalie Bau, Jishnu Das, and Asim I. Khwaja. Heterogeneity in School Value-Added and the Private Premium. Research on Improving Systems of Education (RISE), 2022. http://dx.doi.org/10.35489/bsg-risewp_2022/116.
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Using rich panel data from Pakistan, we compute test score based measures of quality (School Value-Addeds or SVAs) for more than 800 schools across 112 villages and verify that they are valid and unbiased. With the SVA measures, we then document three striking features of the schooling environment. First, there is substantial within-village variation in quality. The annualized difference in learning between the best and worst performing school in the same village is 0.4 sd; compounded over 5 years of primary schooling, this difference is similar in size to the test score gap between low- and high-income countries. Second, students learn more in private schools (0.15 sd per year on average), but substantial within-sector variation in quality means that the effects of reallocating students from public to private schools can range from -0.35sd to +0.65sd. Thus, there is a range of possible causal estimates of the private premium, a feature of the environment we illustrate using three different identification approaches. Finally, parents appear to recognize and reward SVA in the private sector, but the link between parental demand and SVA is weaker in the public sector. These results have implications for both the measurement of the private premium and how we design and evaluate policies that reallocate children across schools, such as school closures and vouchers.
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Putriastuti, Massita Ayu Cindy, Vivi Fitriyanti, and Muhammad Razin Abdullah. Leveraging the Potential of Crowdfunding for Financing Renewable Energy. Purnomo Yusgiantoro Center, 2021. http://dx.doi.org/10.33116/br.002.
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• Renewable energy (RE) projects in Indonesia usually have IRR between 10% and 15% and PP around 6 to 30 years • Attractive return usually could be found in large scale RE projects, although there are numerous other factors involved including technology developments, capacity scale, power purchasing price agreements, project locations, as well as interest rates and applied incentives. • Crowdfunding (CF) has big potential to contribute to the financing of RE projects especially financing small scale RE projects. • P2P lending usually targeted short-term loans with high interest rates. Therefore, it cannot be employed as an alternative financing for RE projects in Indonesia. • Three types of CF that can be employed as an alternative for RE project funding in Indonesia. Namely, securities, reward, and donation-based CF. In addition, hybrid models such as securities-reward and reward-donation could also be explored according to the project profitability. • Several benefits offer by securities crowdfunding (SCF) compared to conventional banking and P2P lending, as follows: (1) issuer do not need to pledge assets as collateral; (2) do not require to pay instalment each month; (3) issuer share risks with investors with no obligation to cover the investor’s loss; (4) applicable for micro, small, medium, enterprises (MSMEs) with no complex requirements; and (5) there is possibility to attract investors with bring specific value. • Several challenges that need to be tackled such as the uncertainty of RE regulations; (1) issuer’s inability in managing the system and business; (2) the absence of third parties in bridging between CF platform and potential issuer from RE project owner; (3) the lack of financial literacy of the potential funders; and (4) lastly the inadequacy of study regarding potential funders in escalating the RE utilisation in Indonesia.
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Riggs, William, Vipul Vyas, and Menka Sethi. Blockchain and Distributed Autonomous Community Ecosystems: Opportunities to Democratize Finance and Delivery of Transport, Housing, Urban Greening and Community Infrastructure. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2165.
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This report investigates and develops specifications for using blockchain and distributed organizations to enable decentralized delivery and finance of urban infrastructure. The project explores use cases, including: providing urban greening, street or transit infrastructure; services for street beautification, cleaning and weed or graffiti abatement; potential ways of resource allocation ADU; permitting and land allocation; and homeless housing. It establishes a general process flow for this blockchain architecture, which involves: 1) the creation of blocks (transactions); 2) sending these blocks to nodes (users) on the network for an action (mining) and then validation that that action has taken place; and 3) then adding the block to the blockchain. These processes involve the potential for creating new economic value for cities and neighborhoods through proof-of-work, which can be issued through a token (possibly a graphic non-fungible token), certificate, or possible financial reward. We find that encouraging trading of assets at the local level can enable the creation of value that could be translated into sustainable “mining actions” that could eventually provide the economic backstop and basis for new local investment mechanisms or currencies (e.g., local cryptocurrency). These processes also provide an innovative local, distributed funding mechanism for transportation, housing and other civic infrastructure.
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Kennedy, James J., Richard W. Haynes, and Xiaoping Zhou. Line officers' views on stated USDA Forest Service values and the agency reward system. U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 2005. http://dx.doi.org/10.2737/pnw-gtr-632.
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Bergeron, Diane. Organizational Wives – The Career Costs of Helping. Center for Creative Leadership, 2025. https://doi.org/10.35613/ccl.2025.2063.
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"Despite comprising nearly half of the global workforce, women are still underrepresented in executive roles across industries and countries. Of the 5,400 companies listed in the S&P Global Corporate Sustainability Assessment, less than 5% had a woman CEO. Although various explanations for gender disparities in career outcomes have been suggested, including unconscious bias, stereotypes, and greater domestic responsibilities, a less explored factor is women's greater engagement in workplace helping. These workplace helping behaviors are known as organizational citizenship behavior (OCB) and are behaviors that exceed job requirements and contribute to the organization. Examples include orienting new employees, helping others accomplish their work, speaking up with suggestions or ideas for improvements, and managing the social environment. These behaviors are positively related to group and organizational performance, efficiency, customer satisfaction, and the quality and quantity of organizational output. Although crucial for organizational functioning, engaging in too much OCB can result in personal sacrifices, such as work-family conflict and working longer hours. OCB can also detract from job behaviors that are more directly linked to rewards and career advancement. Thus, OCB can come at a cost to employees. Research shows that women are expected to engage in more communal, time-consuming OCB than men. Women also receive more requests for help than men and are ‘volunteered’ more for low-promotability tasks. In addition to facing higher expectations, women are often penalized for not performing OCB and receive fewer rewards than men for these behaviors. As such, women often assume a ‘wifely’ role in organizations by taking on necessary, but often invisible, activities that help keep the organization functioning effectively. Gendered expectations, workloads, and rewards result in women shouldering a heavier burden of helping – both at work and at home – which requires more resources and limits their ability to focus on more rewarded tasks that can advance their careers. Women of color face an additional racial burden, known as cultural taxation, where they are expected to take on helping behaviors that assist others of the same race, further impacting their career outcomes. Over time – and across women, organizations, and societies – this collective imbalance restricts women’s global access to power and influence in decision-making. This paper calls for a reevaluation of organizational structures and cultures that maintain inequities, urging a shift from focusing on ""fixing"" women to addressing systemic issues. It calls for organizations and leaders to recognize the value of OCB while ensuring that such work is distributed fairly, paving the way for a more equitable workplace and improved organizational outcomes. This will help enable women to make more meaningful contributions and have greater ability to advocate for organizational and societal changes in the world."
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Millison, Dan, and Kee-Yung Nam. Emerging Hydrogen Energy Technology and Global Momentum. Asian Development Bank, 2024. http://dx.doi.org/10.22617/wps240403-2.
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This paper provides an overview of the emerging hydrogen economy to help decision-makers navigate the green hydrogen value chain, understand what is required for successful implementation, and reap the potential rewards in the energy transition. Green hydrogen is a “power-to-X” business proposition based on selling molecules rather than selling electrons. The financial viability of green hydrogen production depends primarily on electrolyzer costs, local electricity input costs, specific end-use applications, and willingness of hydrogen buyers to commit to long-term offtake agreements. As global electrolyzer manufacturing capacity increases, a virtuous cycle of development may emerge.
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Zhou, Edward W., Paula G. Chaves da Silva, Debbie Quijada, and Fred D. Ledley. Considering Returns on Federal Investment in the Negotiated “Maximum Fair Price” of Drugs Under the Inflation Reduction Act: an Analysis. Institute for New Economic Thinking Working Paper Series, 2024. http://dx.doi.org/10.36687/inetwp219.
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The Inflation Reduction Act (IRA) of 2022 contained landmark provisions authorizing government to negotiate a “maximum fair price” for selected Medicare Part D drugs considering the manufacturer’s research and development costs, federal support for discovery and development, the extent to which the drugs address unmet medical needs, and other factors. This working paper describes federal investment in the discovery and development of the ten drugs selected for price negotiation in the first year of the IRA as well as the health value created through Medicare Part D spending on these drugs. We identified $11.7 billion in NIH funding for basic or applied research leading to approval of these drugs with median investment costs of $895.4 million/drug. This early public investment provided a median cost savings to industry of $1,485 million/drug, comparable to reported levels of investment by industry. From 2017-2021, Medicare Part D spent $126.4 billion (median $10.7 billion) for these products before rebates. Excluding two products for diabetes, Medicare Part D spending was $97.4 billion and the total health value created was 650,940 QALYs or $67.7 billion (WTP/QALY=$104K) representing a negative residual health value of -$29.7 billion (before rebates). We argue that a negotiated fair price should provide returns on both private and public investments in these products commensurate with the scale and risk of these investments, with the principal return on public sector investments being the residual health value (net price) accruing to those using the product. These empirical data provide a cost basis for negotiating a fair price that rewards early government investments in innovation and provides social value for the public.
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Kondratenko, Larysa O., Hanna T. Samoylenko, Arnold E. Kiv, et al. Computer simulation of processes that influence adolescent learning motivation. [б. в.], 2021. http://dx.doi.org/10.31812/123456789/4452.
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In order for the learning process to always retain personal value for the learner, it is necessary that his or her motivation be maintained through an awareness of his or her purpose and goals. This article presents a local model (at the individual object level) of enhancing external motivation, which give to determine students’ efforts to get rewards. The concept of this model based on describing the behavior of agents (in our case students). The characteristics of the phenomenon in the motivation of learning at different stages of adolescent development are analyzed. The problem of computer modeling of educational processes with the help of agent modeling on the example of studying student motivation is considered. Internal and external factors that may strengthen or weaken the adolescent’s motivation to study have been studied. The expediency of using information technologies of agent modeling to study the dynamics of strengthening or weakening student motivation is substantiated. Using the AnyLogic Cloud computing environment the change of dynamics of strengthening of motivation of teenagers on an example of model of strengthening of external motivation is defined.
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Kotula, Hannah. Valuing forest ecosystem services in New Zealand. Motu Economic and Public Policy Research, 2022. http://dx.doi.org/10.29310/wp.2022.11.
Full textAbstract:
Society depends on services and benefits provided by ecosystems. Yet, many of our actions affect ecosystems in ways that undermine long-term human wellbeing. Although ecosystems provide many services to society, many of these services are not accounted for in land-use decisions. The concept of “ecosystem services” offers a framework for understanding our dependence on nature and can encourage decision makers to consider broader impacts of land-use decisions beyond short-term economic rewards. Furthermore, economic valuation of ecosystem services offers a potential strategy for including the value of ecosystem services in decision making. Here I describe several ecosystem service frameworks and outline how these frameworks can inform land-use decisions, with a particular focus on those involving forests. I then describe methods for valuing ecosystem services. Following this, I provide examples relating to forest ecosystem services and draw conclusions based on existing valuation studies in New Zealand. My intention is to convey how an ecosystem service approach could be used in New Zealand to capture benefits provided by ecosystems that are often not accounted for in land-use decisions.