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Adaptive Proposer for Ultimatum Game
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SYSNO ASEP 0462888 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Adaptive Proposer for Ultimatum Game Author(s) Hůla, František (UTIA-B)
Ruman, Marko (UTIA-B)
Kárný, Miroslav (UTIA-B) RID, ORCIDNumber of authors 3 Source Title Artificial Neural Networks and Machine Learning – ICANN 2016, Part I.. - Cham : Springer, 2016 - ISSN 0302-9743 - ISBN 978-3-319-44777-3 Pages s. 330-338 Number of pages 8 s. Publication form Print - P Action International Conference on Artificial Neural Networks 2016 /25./ Event date 06.09.2016 - 09.09.2016 VEvent location Barcelona Country ES - Spain Event type WRD Language eng - English Country CH - Switzerland Keywords Games ; Markov decision process ; Bayesian learning Subject RIV BB - Applied Statistics, Operational Research R&D Projects GA13-13502S GA ČR - Czech Science Foundation (CSF) Institutional support UTIA-B - RVO:67985556 UT WOS 000389086300039 EID SCOPUS 84988039951 DOI 10.1007/978-3-319-44778-0_39 Annotation Ultimate Game serves for extensive studies of various aspects of human decision making. The current paper contribute to them by designing proposer optimising its policy using Markov-decision-process (MDP) framework combined with recursive Bayesian learning of responder’s model. Its foreseen use: i) standardises experimental conditions for studying rationality and emotion-influenced decision making of human responders; ii) replaces the classical game-theoretical design of the players’ policies by an adaptive MDP, which is more realistic with respect to the knowledge available to individual players and decreases player’s deliberation effort; iii) reveals the need for approximate learning and dynamic programming inevitable for coping with the curse of dimensionality; iv) demonstrates the influence of the fairness attitude of the proposer on the game course; v) prepares the test case for inspecting exploration-exploitation dichotomy. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2017
Number of the records: 1