000			03637nam a22003975i 4500
001			295157
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007			cr nn 008mamaa
008			150903s2005 gw | o |||| 0|eng d
020			_a9783540322740 _99783540322740
024	7		_a10.1007/b106974 _2doi
035			_avtls000348296
039		9	_a201509030445 _bVLOAD _c201405070459 _dVLOAD _y201402071024 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQ334-342
100	1		_aKudenko, Daniel. _eeditor. _9329362
245	1	0	_aAdaptive Agents and Multi-Agent Systems II : _bAdaptation and Multi-Agent Learning / _cedited by Daniel Kudenko, Dimitar Kazakov, Eduardo Alonso.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2005.
300			_aviii, 313 páginas Also available online. _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aLecture Notes in Computer Science, _x0302-9743 ; _v3394
500			_aSpringer eBooks
505	0		_aGödel Machines: Towards a Technical Justification of Consciousness -- Postext – A Mind for Society -- Comparing Resource Sharing with Information Exchange in Co-operative Agents, and the Role of Environment Structure -- Baselines for Joint-Action Reinforcement Learning of Coordination in Cooperative Multi-agent Systems -- SMART (Stochastic Model Acquisition with ReinforcemenT) Learning Agents: A Preliminary Report -- Towards Time Management Adaptability in Multi-agent Systems -- Learning to Coordinate Using Commitment Sequences in Cooperative Multi-agent Systems -- Reinforcement Learning of Coordination in Heterogeneous Cooperative Multi-agent Systems -- Evolving the Game of Life -- The Strategic Control of an Ant-Based Routing System Using Neural Net Q-Learning Agents -- Dynamic and Distributed Interaction Protocols -- Advice-Exchange Between Evolutionary Algorithms and Reinforcement Learning Agents: Experiments in the Pursuit Domain -- Evolving Strategies for Agents in the Iterated Prisoner’s Dilemma in Noisy Environments -- Experiments in Subsymbolic Action Planning with Mobile Robots -- Robust Online Reputation Mechanism by Stochastic Approximation -- Learning Multi-agent Search Strategies -- Combining Planning with Reinforcement Learning for Multi-robot Task Allocation -- Multi-agent Reinforcement Learning in Stochastic Single and Multi-stage Games -- Towards Adaptive Role Selection for Behavior-Based Agents.
520			_aAdaptive agents and multi-agent systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, software engineering, and developmental biology, as well as cognitive and social science. This book presents 17 revised and carefully reviewed papers taken from two workshops on the topic as well as 2 invited papers by leading researchers in the area. The papers deal with various aspects of machine learning, adaptation, and evolution in the context of agent systems and autonomous agents.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aKazakov, Dimitar. _eeditor. _9329363
700	1		_aAlonso, Eduardo. _eeditor. _9329364
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783540252603
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/b106974 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c295157 _d295157