| 书目名称 | Sample Efficient Multiagent Learning in the Presence of Markovian Agents |
| 编辑 | Doran Chakraborty |
| 视频video | |
| 概述 | Presents recent research in sample efficient multiagent learning in the presence of markovian agents.Develops multiagent learning algorithms not previously been achieved.Takes steps towards building c |
| 丛书名称 | Studies in Computational Intelligence |
| 图书封面 |  |
| 描述 | The problem of Multiagent Learning (or MAL) is concerned with the study of how intelligent entities can learn and adapt in the presence of other such entities that are simultaneously adapting. The problem is often studied in the stylized settings provided by repeated matrix games (a.k.a. normal form games). The goal of this book is to develop MAL algorithms for such a setting that achieve a new set of objectives which have not been previously achieved. In particular this book deals with learning in the presence of a new class of agent behavior that has not been studied or modeled before in a MAL context: Markovian agent behavior. Several new challenges arise when interacting with this particular class of agents. The book takes a series of steps towards building completely autonomous learning algorithms that maximize utility while interacting with such agents. Each algorithm is meticulously specified with a thorough formal treatment that elucidates its key theoretical properties. |
| 出版日期 | Book 2014 |
| 关键词 | Computational Intelligence; Markovian Agents; Multiagent Learning Algorithms; Sample Efficient Multiage |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-02606-0 |
| isbn_softcover | 978-3-319-35293-0 |
| isbn_ebook | 978-3-319-02606-0Series ISSN 1860-949X Series E-ISSN 1860-9503 |
| issn_series | 1860-949X |
| copyright | Springer International Publishing Switzerland 2014 |
发表于 2025-3-21 17:50:02
