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_aT57.95 _bO454 2016 |
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_aOliehoek, Frans A. _998550 _0Local |
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| 245 | 1 | 2 |
_aA Concise Introduction to Decentralized POMDPs _cby Frans A Oliehoek, Christopher Amato |
| 260 |
_aCham _bSpringer International Publishing _c2016 |
||
| 300 |
_a1 recurso en línea (XX, 134 páginas) _b36 ilustraciones, 22 ilustraciones en color |
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| 336 |
_aTexto _btxt _2rdacontent |
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| 337 |
_aelectrónico _bc _2rdamedia |
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| 338 |
_arecurso electrónico _bcr _2rdacarrier |
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| 490 | 0 |
_aSpringerBriefs in Intelligent Systems, Artificial Intelligence, Multiagent Systems, and Cognitive Robotics _x2196-548X |
|
| 505 | 0 | _aMultiagent Systems Under Uncertainty -- The Decentralized POMDP Framework -- Finite-Horizon Dec-POMDPs -- Exact Finite-Horizon Planning Methods -- Approximate and Heuristic Finite-Horizon Planning Methods -- Infinite-Horizon Dec-POMDPs -- Infinite-Horizon Planning Methods: Discounted Cumulative Reward -- Infinite-Horizon Planning Methods: Average Reward -- Further Topics. | |
| 520 | 3 | _aThis book introduces multiagent planning under uncertainty as formalized by decentralized partially observable Markov decision processes (Dec-POMDPs). The intended audience is researchers and graduate students working in the fields of artificial intelligence related to sequential decision making: reinforcement learning, decision-theoretic planning for single agents, classical multiagent planning, decentralized control, and operations research. . | |
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_aSpringerLink (Online service) _0Local _9106996 |
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| 988 | _aEBOOK, asignarmaterias , EBSPRINGER | ||
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_aInteligencia artificial _0comprobar BNE19900997218 _2embne _9413115 |
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| 650 | 7 |
_9145705 _aOptimización matemática _0comprobar BNE19922522034 _2embne |
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| 700 | 1 |
_aAmato, Christopher _0Local _998551 |
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| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-28929-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
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