Academic literature on the topic 'Exploitation e exploration'
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Journal articles on the topic "Exploitation e exploration"
Kim, Andrea. "Human resource strategies for organizational ambidexterity." Employee Relations: The International Journal 41, no. 4 (June 3, 2019): 678–93. http://dx.doi.org/10.1108/er-09-2017-0228.
Full textCordes, Erik E., and Lisa A. Levin. "Exploration before exploitation." Science 359, no. 6377 (February 15, 2018): 719. http://dx.doi.org/10.1126/science.aat2637.
Full textZhao, Haiyuan, and Xiaobao Peng. "Exploitation versus exploration." Chinese Management Studies 12, no. 3 (August 6, 2018): 547–74. http://dx.doi.org/10.1108/cms-09-2017-0278.
Full textIheanacho, Ike. "Exploration or exploitation?" BMJ 334, no. 7588 (February 8, 2007): 317. http://dx.doi.org/10.1136/bmj.39097.733461.59.
Full textLee, Jongseon, and Nami Kim. "Know yourself and find your partners." Management Research Review 42, no. 12 (December 9, 2019): 1333–52. http://dx.doi.org/10.1108/mrr-06-2018-0244.
Full textZhang, Huiying, and Shuang Lv. "Effect of HR practice on NPD performance." Nankai Business Review International 6, no. 3 (August 3, 2015): 256–80. http://dx.doi.org/10.1108/nbri-03-2015-0008.
Full textJiang, Jiechuan, and Zongqing Lu. "Generative Exploration and Exploitation." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 4337–44. http://dx.doi.org/10.1609/aaai.v34i04.5858.
Full textSCHULZE, PATRICK, FLORIAN HEINEMANN, and ANNAS ABEDIN. "BALANCING EXPLOITATION AND EXPLORATION." Academy of Management Proceedings 2008, no. 1 (August 2008): 1–6. http://dx.doi.org/10.5465/ambpp.2008.33622934.
Full textvan Dooren, Roel, Roy de Kleijn, Bernhard Hommel, and Zsuzsika Sjoerds. "The exploration-exploitation trade-off in a foraging task is affected by mood-related arousal and valence." Cognitive, Affective, & Behavioral Neuroscience 21, no. 3 (June 2021): 549–60. http://dx.doi.org/10.3758/s13415-021-00917-6.
Full textJIANG, YANHUI, CHONGYANG WEI, ZHI YANG, and ULAGANATHAN SUBRAMANIAN. "DOES STRONGER R&D CAPABILITY ALWAYS PROMOTE BETTER INNOVATION? THE MODERATING ROLE OF KNOWLEDGE BOUNDARY SPANNING OF R&D NETWORK." International Journal of Innovation Management 22, no. 07 (October 2018): 1850059. http://dx.doi.org/10.1142/s1363919618500597.
Full textDissertations / Theses on the topic "Exploitation e exploration"
Atwi, Aliaa. "Exploration vs. exploitation in coupon personalization." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/115729.
Full textCataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 51-52).
Personalized offers aim to maximize profit by taking into account customer preferences inferred from past purchase behavior. For large retailers with extensive product offerings, learning customer preferences can be challenging due to relatively short purchase histories of most customers. To alleviate the dearth of data, we propose exploiting similarities among products and among customers to reduce problem dimensions. We also propose that retailers use personalized offers not only to maximize expected profit, but to actively learn their customers' preferences. An offer that does not maximize expected profit given current information may still provide valuable insights about customer preferences. This information enables more profitable coupon allocation and higher profits in the long run. In this thesis we 1) derive approximate inference algorithms to learn customer preferences from purchase data in real time, 2) formulate the retailers' offer allocation problem as a multi armed bandit and explore solution strategies.
by Aliaa Atwi.
Elec. E. in Computer Science
Adelsbo, Felix. "Exploration and Exploitation in Reinforcement Learning." Thesis, KTH, Skolan för teknikvetenskap (SCI), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235841.
Full textInom förstärkande inlärning existerar ett dilemma inom utforskningkontra utnyttjande. Detta har lett till utvecklandet av metoder som har olika tillvägagångssätt för detta. Att använda olika typer av metoder, och modifiera dem på olika sätt kan leda till olika resultat. Kunskap om hur olika metoder fungerar kan ge kunskap om vad som ska användas i ett specifikt fall.Två sätt som metoder kan modifieras är ändring i justerbara parametrar och ändring i antalet slumpmässiga steg i början. Hur mycket dessa två modifieringar påverkar resultatet i en specifik miljö kan skilja sig mycketåt, och kan vara en väldigt kritisk sak att betänka för ett visst resultat.Målet med denna studie är att besvara frågan om hur prestandan på de olika metoderna random, greedy, e- greedy e-decreasing och Softmax påverkas av olika värden på deras justerbara parametrar, och av antaletslumpmässiga steg i början. Simuleringarna och en jämförande analys utförs för fallet med en inverterad pendel med en vertikal stolpe placerad på en rörlig vagn.
Bouhlel, Imen. "Essais sur le dilemme exploration-exploitation." Thesis, Université Côte d'Azur (ComUE), 2019. http://theses.univ-cotedazur.fr/2019AZUR0037.
Full textA growing body of empirical evidence during the two last decades has been showing inconsistencies between individual choices when the individuals make decisions from description (i.e., when they are provided with a perfect knowledge about the states space, including all the possible outcomes, and the underlying probabilities), compared to when they make decisions from experience (i.e., when they do not know all the possible outcomes or/and their occurrence probabilities). These inconsistencies are referred to as the description/experience gap. Undersearch has been pointed out as one of the key determinants of this gap. Hence, even though little studied in economics, search becomes a central question, deserving serious interest. This thesis aims at contributing to the theoretical and experimental literature studying search and the related exploration-exploitation dilemma, both at the individual and at the collective level. The thesis is made of 3 essays, combining theoretical, agent-based modelling, evolutionary simulations and laboratory experiments. The first chapter of this thesis examines the determinants of search behavior in the context of an individual optimal stopping problem and shows that this behavior largely depends on the degree of certainty of the information, and is affected by both regret and anticipation. The second chapter investigates information sharing behavior in competitive collective search using agent-based and evolutionary simulations. It finds robust evidence for the individual benefits of sharing, even when others do not reciprocate, as long as two mechanisms as present: Imitation with a certain level of innovation and local visibility. The third chapter experimentally tests and supports the validity of theses results, and stresses the crucial role of learning
Ozcan, Ozkan. "Balancing exploration and exploitation in agent learning." Thesis, Monterey, California. Naval Postgraduate School, 2011. http://hdl.handle.net/10945/5468.
Full textControlling the ratio of exploration and exploitation in agent learning in dynamic environments is a continuing challenge in applying agent-learning techniques. Methods to control this ratio in a manner that mimics human behavior are required for use in the representation of human behavior in simulations, where the goal is to constrain agent-learning mechanisms in a manner similar to that observed in human cognition. The Cultural Geography (CG) model, under development in TRAC Monterey, is an agent-based social simulation. It simulates a wide variety of situations and scenarios so that a dynamic ratio between exploration and exploitation makes the decisions more sensible. As part of an attempt to improve the model, this thesis investigates enhancements to the exploration-exploitation balance by using different techniques. The work includes design of experiments with a range of factors in multiple environments and statistical analysis related to these experiments. As a main finding from this research, for small environments and for short runs techniques based on subjective utility give better results, while for long runs techniques based on time obtain higher utilities than other techniques. In more complex and bigger environments, a combined technique performed better in long runs.
Lampela, T. (Teemu). "Modelling exploration and exploitation in organizational learning." Bachelor's thesis, University of Oulu, 2019. http://jultika.oulu.fi/Record/nbnfioulu-201904271553.
Full textPickering, Andrew Christopher. "An empirical analysis of the exploitation of oil." Thesis, University of Exeter, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248158.
Full textFaroque, Anisur Rahman. "Network exploration and exploitation in international entrepreneurship: an opportunity-based view." Thesis, University of Canterbury. Department of Management, Marketing & Entrepreneurship, 2014. http://hdl.handle.net/10092/9639.
Full textLiedholm, Johnson Eva. "Mineral Rights : Legal Systems Governing Exploration and Exploitation." Doctoral thesis, KTH, Fastighetsvetenskap, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-12044.
Full textQC20100723
Abeille, Marc. "Exploration-exploitation with Thompson sampling in linear systems." Thesis, Lille 1, 2017. http://www.theses.fr/2017LIL10182/document.
Full textThis dissertation is dedicated to the study of the Thompson Sampling (TS) algorithms designed to address the exploration-exploitation dilemma that is inherent in sequential decision-making under uncertainty. As opposed to algorithms derived from the optimism-in-the-face-of-uncertainty (OFU) principle, where the exploration is performed by selecting the most favorable model within the set of plausible one, TS algorithms rely on randomization to enhance the exploration, and thus are much more computationally efficient. We focus on linearly parametrized problems that allow for continuous state-action spaces, namely the Linear Bandit (LB) problems and the Linear Quadratic (LQ) control problems. We derive two novel analyses for the regret of TS algorithms in those settings. While the obtained regret bound for LB is similar to previous results, the proof sheds new light on the functioning of TS, and allows us to extend the analysis to LQ problems. As a result, we prove the first regret bound for TS in LQ, and show that the frequentist regret is of order O(sqrt{T}) which matches the existing guarantee for the regret of OFU algorithms in LQ. Finally, we propose an application of exploration-exploitation techniques to the practical problem of portfolio construction, and discuss the need for active exploration in this setting
Shaposhnik, Yaron. "Exploration vs. exploitation : reducing uncertainty in operational problems." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106681.
Full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 205-207).
Motivated by several core operational applications, we introduce a class of multistage stochastic optimization models that capture a fundamental tradeoff between performing work under uncertainty (exploitation) and investing resources to reduce the uncertainty in the decision making (exploration/testing). Unlike existing models, in which the exploration-exploitation tradeoffs typically relate to learning the underlying distributions, the models we introduce assume a known probabilistic characterization of the uncertainty, and focus on the tradeoff of learning exact realizations. In the first part of the thesis (Chapter 2), we study a class of scheduling problems that capture common settings in service environments in which the service provider must serve a collection of jobs that have a-priori uncertain processing times and priorities (modeled as weights). In addition, the service provider must decide how to dynamically allocate capacity between processing jobs and testing jobs to learn more about their respective processing times and weights. We obtain structural results of optimal policies that provide managerial insights, efficient optimal and near-optimal algorithms, and quantification of the value of testing. In the second part of the thesis (Chapter 3), we generalize the model introduced in the first part by studying how to prioritize testing when jobs have different uncertainties. We model difference in uncertainties using the convex order, a general relation between distributions, which implies that the variance of one distribution is higher than the variance of the other distribution. Using an analysis based on the concept of mean preserving local spread, we show that the structure of the optimal policy generalizes that of the initial model where jobs were homogeneous and had equal weights. Finally, in the third part of the thesis (Chapter 4), we study a broad class of stochastic combinatorial optimization that can be formulated as Linear Programs whose objective coefficients are random variables that can be tested, and whose constraint polyhedron has the structure of a polymatroid. We characterize the optimal policy and show that similar types of policies optimally govern testing decisions in this setting as well.
by Yaron Shaposhnik.
Ph. D.
Books on the topic "Exploitation e exploration"
Schulze, Patrick. Balancing Exploitation and Exploration. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8397-8.
Full textStöckmann, Christoph. Exploration und Exploitation in adoleszenten Unternehmen. Wiesbaden: Gabler, 2010. http://dx.doi.org/10.1007/978-3-8349-8644-3.
Full textAsian Mining Conference and Exhibition (4th 1993 Calcutta, India). 4th Asian Mining: Exploration, exploitation and environment. Edited by Singh T. N and Mining, Geological, and Metallurgical Institute of India. New Delhi: Oxford & IBH Pub. Co., 1994.
Find full textTønnessen, Tor. Managing Process Innovation through Exploitation and Exploration. Wiesbaden: Springer Fachmedien Wiesbaden, 2014. http://dx.doi.org/10.1007/978-3-658-04403-9.
Full textThomsen, Leon. Understanding seismic anisotropy in exploration and exploitation. Tulsa, Okla: Society of Exploration Geophysicists, 2002.
Find full textFigueirôa, Silvia Fernanda, Gregory A. Good, and Drielli Peyerl, eds. History, Exploration & Exploitation of Oil and Gas. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13880-6.
Full textA history of the Arctic: Nature, exploration and exploitation. London: Reaktion Books, 2012.
Find full textChaubisa, M. L. Caste, tribe, and exploitation: Exploration of inequality at village level. Udaipur: Himanshu Publications, 1988.
Find full textAAS/JRS Symposium (1st 1985 Honolulu, Hawaii). Space exploitation and utilization: Proceedings of the First AAS/JRS Symposium. San Diego, Calif: Published for the American Astronautical Society by Univelt, 1986.
Find full textThe River Congo: The discovery, exploration, and exploitation of the world's most dramatic river. Boston: Houghton Mifflin Co., 1991.
Find full textBook chapters on the topic "Exploitation e exploration"
Pulido-Bosch, Antonio. "Exploration and Exploitation." In Principles of Karst Hydrogeology, 313–69. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-55370-8_8.
Full textRhee, Mooweon, and Tohyun Kim. "Exploration and Exploitation." In The Palgrave Encyclopedia of Strategic Management, 1–4. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-349-94848-2_388-1.
Full textRhee, Mooweon, and Tohyun Kim. "Exploration and Exploitation." In The Palgrave Encyclopedia of Strategic Management, 543–46. London: Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-137-00772-8_388.
Full textSchulze, Patrick. "Introduction." In Balancing Exploitation and Exploration, 1–14. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8397-8_1.
Full textSchulze, Patrick. "Context, Definitions and Characteristics of Exploitation and Exploration." In Balancing Exploitation and Exploration, 15–29. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8397-8_2.
Full textSchulze, Patrick. "Theoretical Framework." In Balancing Exploitation and Exploration, 30–64. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8397-8_3.
Full textSchulze, Patrick. "Hypotheses and Research Model." In Balancing Exploitation and Exploration, 65–77. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8397-8_4.
Full textSchulze, Patrick. "Methodology of Data Analysis." In Balancing Exploitation and Exploration, 78–115. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8397-8_5.
Full textSchulze, Patrick. "Design of the Research Instrument." In Balancing Exploitation and Exploration, 116–41. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8397-8_6.
Full textSchulze, Patrick. "Data Collection and Data Sample." In Balancing Exploitation and Exploration, 142–53. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8397-8_7.
Full textConference papers on the topic "Exploitation e exploration"
Ahukorala, Kumaripaba, Alan Medlar, Kalle Ilves, and Dorota Glowacka. "Balancing Exploration and Exploitation." In CIKM'15: 24th ACM International Conference on Information and Knowledge Management. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2806416.2806609.
Full textYariv, Leeat. "Disentangling Exploration from Exploitation." In EC '21: The 22nd ACM Conference on Economics and Computation. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3465456.3467524.
Full textChen, JianPing, qiming fu, quan liu, and heng luo. "Single Trajectory Learning: Exploration VS. Exploitation." In MOL2NET 2016, International Conference on Multidisciplinary Sciences, 2nd edition. Basel, Switzerland: MDPI, 2016. http://dx.doi.org/10.3390/mol2net-02-03846.
Full textLiu, Hebin. "Competence Exploration and Exploitation and Innovation." In 2010 International Conference on Management and Service Science (MASS 2010). IEEE, 2010. http://dx.doi.org/10.1109/icmss.2010.5577384.
Full textRickert, Markus, Oliver Brock, and Alois Knoll. "Balancing exploration and exploitation in motion planning." In 2008 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2008. http://dx.doi.org/10.1109/robot.2008.4543636.
Full textKarimzadehgan, Maryam, and ChengXiang Zhai. "Exploration-exploitation tradeoff in interactive relevance feedback." In the 19th ACM international conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1871437.1871631.
Full textLoy, C. C., T. M. Hospedales, Tao Xiang, and Shaogang Gong. "Stream-based joint exploration-exploitation active learning." In 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2012. http://dx.doi.org/10.1109/cvpr.2012.6247847.
Full textJingjing, Ding, Lv Hongjiang, and Zhou Yingtang. "Trust brokerage drives manager's exploration and exploitation." In the 3rd International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3361785.3361787.
Full textBarker, Sydney, Chelsea Sabo, Kelly Cohen, and Cody Lafountain. "Intelligent Algorithms for Maze Exploration and Exploitation." In Infotech@Aerospace 2011. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2011. http://dx.doi.org/10.2514/6.2011-1510.
Full textSimpkins, Alex, Raymond de Callafon, and Emanuel Todorov. "Optimal trade-off between exploration and exploitation." In 2008 American Control Conference (ACC '08). IEEE, 2008. http://dx.doi.org/10.1109/acc.2008.4586462.
Full textReports on the topic "Exploitation e exploration"
Lee, Michael D., and Mark Steyvers. Modeling Exploration and Exploitation in Structured Environments. Fort Belvoir, VA: Defense Technical Information Center, June 2010. http://dx.doi.org/10.21236/ada567393.
Full textScott A. Wood. Behavior of Rare Earth Element In Geothermal Systems; A New Exploration/Exploitation Tool. Office of Scientific and Technical Information (OSTI), January 2002. http://dx.doi.org/10.2172/792697.
Full textKoch, Kaelynn. An investigation of exploitation versus exploration in GBEA optimization of PORS 15 and 16 Problems. Office of Scientific and Technical Information (OSTI), January 2012. http://dx.doi.org/10.2172/1048523.
Full textAldendifer, Elise, McKenzie Coe, Taylor Faught, Ian Klein, Peter Kuylen, Keeli Lane, Robert Loughran, et al. The Safe and Efficient Development of Offshore Transboundary Hydrocarbons: Best Practices from the North Sea and Their Application to the Gulf of Mexico. Edited by Gabriel Eckstein. Texas A&M University School of Law Program in Energy, Environmental, & Natural Resource Systems, September 2019. http://dx.doi.org/10.37419/eenrs.offshoretransboundaryhydrocarbons.
Full textde Caritat, Patrice, Brent McInnes, and Stephen Rowins. Towards a heavy mineral map of the Australian continent: a feasibility study. Geoscience Australia, 2020. http://dx.doi.org/10.11636/record.2020.031.
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