Using HMM in Strategic Games
| Autor: | Pedro Rougemont, Isaque Macalam Saab Lima, Mario R. F. Benevides, Rafael Nader |
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| Rok vydání: | 2014 |
| Předmět: |
FOS: Computer and information sciences
Markov chain business.industry Computer science lcsh:Mathematics I.2.8 ComputingMilieux_PERSONALCOMPUTING ComputerApplications_COMPUTERSINOTHERSYSTEMS Type (model theory) lcsh:QA1-939 lcsh:QA75.5-76.95 Computer Science - Information Retrieval Odds Machine Learning (cs.LG) Moment (mathematics) Computer Science - Learning Computer Science - Computer Science and Game Theory lcsh:Electronic computers. Computer science Artificial intelligence business Hidden Markov model Information Retrieval (cs.IR) Computer Science and Game Theory (cs.GT) |
| Zdroj: | DCM Electronic Proceedings in Theoretical Computer Science, Vol 144, Iss Proc. DCM 2013, Pp 73-84 (2014) |
| DOI: | 10.48550/arxiv.1404.0086 |
| Popis: | In this paper we describe an approach to resolve strategic games in which players can assume different types along the game. Our goal is to infer which type the opponent is adopting at each moment so that we can increase the player's odds. To achieve that we use Markov games combined with hidden Markov model. We discuss a hypothetical example of a tennis game whose solution can be applied to any game with similar characteristics. Comment: In Proceedings DCM 2013, arXiv:1403.7685 |
| Databáze: | OpenAIRE |
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