Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Joo, Haram | - |
dc.contributor.author | Jeong, Inhyeok | - |
dc.contributor.author | Baek, Jong Woo | - |
dc.contributor.author | Lee, Sang Wan | - |
dc.date.accessioned | 2024-02-22T09:40:14Z | - |
dc.date.available | 2024-02-22T09:40:14Z | - |
dc.date.created | 2023-04-27 | - |
dc.date.issued | 2022-11-30 | - |
dc.identifier.isbn | 9781665499248 | - |
dc.identifier.issn | 2377-6870 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11750/47981 | - |
dc.description.abstract | Most of the studies on model-based reinforcement learning (RL) have been confined to single agent learning scenarios. This impedes us from fully exploring the nature and potential of model-based RL. In this study, we design a simple model-based RL agent capable of performing multi-agent tasks and evaluate the ability of model-based RL using various types of iterative Keynesian beauty contests. We examined its characteristics from various perspectives, including dominance in the competition as a performance measure, evolutionary process as an adaptation measure, the rate of convergence to the Nash equilibrium as a basic measure of effectiveness, and the degree of cooperation as an alternative measure of it. Simulations showed that the model-based RL agent outperforms other types of agents, including rule-based methods and model-free RL, by all measures. © 2022 IEEE. | - |
dc.language | English | - |
dc.publisher | Japan Society for Fuzzy Theory and intelligent informatics (SOFT) | - |
dc.title | Predicting Other's Minds Using Model-based Reinforcement Learning | - |
dc.type | Conference Paper | - |
dc.identifier.doi | 10.1109/SCISISIS55246.2022.10001864 | - |
dc.identifier.scopusid | 2-s2.0-85146662233 | - |
dc.identifier.bibliographicCitation | Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, SCIS & ISIS 2022, pp.1 - 6 | - |
dc.identifier.url | https://soft-cr.org/scis/2022/program.html#w-1-g-gs-reinforcement-learning:~:text=%5BFull%20paper%5D-,Predicting%20Other%E2%80%99s,-Minds%20Using%20Model | - |
dc.citation.conferencePlace | JA | - |
dc.citation.conferencePlace | Ise-Shima | - |
dc.citation.endPage | 6 | - |
dc.citation.startPage | 1 | - |
dc.citation.title | Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, SCIS & ISIS 2022 | - |
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