Sample Efficient Multiagent Learning in the Presence of Markovian Agents (Record no. 57770)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02907nam a22004695i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-319-02606-0 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20200421112227.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 130930s2014 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783319026060 |
| -- | 978-3-319-02606-0 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.3 |
| 100 1# - AUTHOR NAME | |
| Author | Chakraborty, Doran. |
| 245 10 - TITLE STATEMENT | |
| Title | Sample Efficient Multiagent Learning in the Presence of Markovian Agents |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XVIII, 147 p. 31 illus. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Studies in Computational Intelligence, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Introduction -- Background -- Learn or Exploit in Adversary Induced Markov Decision Processes -- Convergence, Targeted Optimality and Safety in Multiagent Learning -- Maximizing -- Targeted Modeling of Markovian agents -- Structure Learning in Factored MDPs -- Related Work -- Conclusion and Future Work. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-319-02606-0 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2014. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Engineering. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational intelligence. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Engineering. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial Intelligence (incl. Robotics). |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 1860-949X ; |
| 912 ## - | |
| -- | ZDB-2-ENG |
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