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Adaptive Agents and Multi-Agent Systems II Adaptation and Multi-Agent Learning - Kudenko, Daniel (Herausgeber); Alonso, Eduardo (Herausgeber); Kazakov, Dimitar (Herausgeber)
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Kudenko, Daniel (Herausgeber); Alonso, Eduardo (Herausgeber); Kazakov, Dimitar (Herausgeber):

Adaptive Agents and Multi-Agent Systems II Adaptation and Multi-Agent Learning - nuovo libro

2005, ISBN: 3540252606

2005 Kartoniert / Broschiert Agent (EDV) - Agentensystem, Adaption, Anpassung (allgemein), Intelligenz / Künstliche Intelligenz, KI, Künstliche Intelligenz - AI, Compiler und Übersetzer… Altro …

Costi di spedizione:Versandkostenfrei innerhalb der BRD. (EUR 0.00) MARZIES.de Buch- und Medienhandel, 14621 Schönwalde-Glien
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Adaptive Agents and Multi-Agent Systems II: Adaptation and Multi-Agent Learning (Lecture Notes in Computer Science, 3394, Band 3394) - Kudenko, Daniel, Alonso, Eduardo, Kazakov, Dimitar
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Kudenko, Daniel, Alonso, Eduardo, Kazakov, Dimitar:

Adaptive Agents and Multi-Agent Systems II: Adaptation and Multi-Agent Learning (Lecture Notes in Computer Science, 3394, Band 3394) - edizione con copertina flessibile

2008, ISBN: 9783540252603

Springer, Taschenbuch, Auflage: 2005, 324 Seiten, Publiziert: 2008-06-13T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: Illustrations, 1.02 kg, Hardware & Technik, Computer & Internet, K… Altro …

Costi di spedizione:Auf Lager, Lieferung von Amazon. (EUR 0.00) Amazon.de
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Adaptive Agents a Adaptation and Multi-Agent Learning - Kudenko, Daniel (Herausgeber)
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Kudenko, Daniel (Herausgeber):
Adaptive Agents a Adaptation and Multi-Agent Learning - edizione con copertina flessibile

2005

ISBN: 3540252606

[EAN: 9783540252603], Gebraucht, wie neu, [SC: 12.97], [PU: Springer Berlin], Lecture Notes Computer Science 33941. Ed.2005VIII, 313 S. - 23,50 x 15,50 cm; Gewicht: 463g , originalverpack… Altro …

NOT NEW BOOK. Costi di spedizione: EUR 12.97 Buecherhof, Brekendorf, Germany [52752108] [Rating: 5 (von 5)]
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Kudenko, Daniel [Editor]; Kazakov, Dimitar [Editor]; Alonso, Eduardo [Editor];:
Adaptive Agents and Multi-Agent Systems II: Adaptation and Multi-Agent Learning (Lecture Notes in Computer Science) - edizione con copertina flessibile

2005, ISBN: 3540252606

[EAN: 9783540252603], Gebraucht, sehr guter Zustand, [PU: Springer], Ex-library paperback in very nice condition with the usual markings and attachments., Books

NOT NEW BOOK. Costi di spedizione: EUR 41.41 GuthrieBooks, Spring Branch, TX, U.S.A. [52069477] [Rating: 5 (von 5)]
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Kudenko, Daniel (Editor), and Kazakov, Dimitar (Editor), and Alonso, Eduardo (Editor):
Adaptive Agents and Multi-Agent Systems II: Adaptation and Multi-Agent Learning - edizione con copertina flessibile

2005, ISBN: 9783540252603

Trade paperback, New., Trade paperback (US). Glued binding. 313 p., Berlin, Heidelberg, [PU: Springer]

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Dettagli del libro
Adaptive Agents and Multi-Agent Systems II: Adaptation and Multi-Agent Learning (Lecture Notes in Computer Science, 3394, Band 3394)
Autore:
Titolo:
ISBN:

3540252606


Adaptive 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.

Informazioni dettagliate del libro - Adaptive Agents and Multi-Agent Systems II: Adaptation and Multi-Agent Learning (Lecture Notes in Computer Science, 3394, Band 3394)


EAN (ISBN-13): 9783540252603
ISBN (ISBN-10): 3540252606
Copertina flessibile
Anno di pubblicazione: 2005
Editore: Springer
328 Pagine
Peso: 0,497 kg
Lingua: eng/Englisch

Libro nella banca dati dal 2007-05-29T03:43:41+02:00 (Rome)
Pagina di dettaglio ultima modifica in 2024-02-22T16:01:50+01:00 (Rome)
ISBN/EAN: 3540252606

ISBN - Stili di scrittura alternativi:
3-540-25260-6, 978-3-540-25260-3
Stili di scrittura alternativi e concetti di ricerca simili:
Autore del libro : kazakov, alonso, dan alon, kazako, kuden
Titolo del libro: adaptive agents multi agent systems, adaptation, agent band, learning learning, adaptiv

Dati dell'editore

Autore: Daniel Kudenko; Dimitar Kazakov; Eduardo Alonso
Titolo: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence; Adaptive Agents and Multi-Agent Systems II - Adaptation and Multi-Agent Learning
Editore: Springer; Springer Berlin
313 Pagine
Anno di pubblicazione: 2005-03-04
Berlin; Heidelberg; DE
Lingua: Inglese
53,49 € (DE)
54,99 € (AT)
59,00 CHF (CH)
Available
VIII, 313 p.

BC; Hardcover, Softcover / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; Informatik; agents; artificial intelligence; autonomous agent; evolution; intelligence; learning; machine learning; multi-agent system; Artificial Intelligence; Software Engineering; Computer Communication Networks; Computer Science Logic and Foundations of Programming; Compilers and Interpreters; User Interfaces and Human Computer Interaction; Software Engineering; Netzwerk-Hardware; Theoretische Informatik; Compiler und Übersetzer; Mensch-Computer-Interaktion; EA

Gödel 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.
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