Relevant bibliographies by topics / Reward value

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Reward value'

Author: Grafiati
Published: 5 June 2025
Last updated: 16 July 2025

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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
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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 co
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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 br
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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
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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 em
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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
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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 v
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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 o
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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 los
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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.
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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 behaviou
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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
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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 t
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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,
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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 t
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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 ar
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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
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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
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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.

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Book 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.

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Conference 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 specifie
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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 proc
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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 (
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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. O
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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
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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.

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Reports 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 h
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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. Therefor
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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 bl
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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&amp;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) an
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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 globa
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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
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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
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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.

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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 va
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