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Learning and Adaption in Multi-Agent Systems - 15 Angebote vergleichen
Preise | 2016 | 2019 | 2021 |
---|---|---|---|
Schnitt | € 57,69 | € 50,01 | € 68,97 |
Nachfrage |
Learning and Adaption in Multi-Agent Systems (2005)
ISBN: 9783540330530 bzw. 3540330534, vermutlich in Englisch, Springer Nature, Taschenbuch, neu.
This book contains selected and revised papers of the International Workshop on Lea- ing and Adaptation in Multi-Agent Systems (LAMAS 2005), held at the AAMAS 2005 Conference in Utrecht, The Netherlands, July 26. An important aspect in multi-agent systems (MASs) is that the environment evolves over time, not only due to external environmental changes but also due to agent int- actions. For this reason it is important that an agent can learn, based on experience, and adapt its knowledge to make rational decisions and act in this changing environment autonomously. Machine learning techniques for single-agent frameworks are well established. Agents operate in uncertain environments and must be able to learn and act - tonomously. This task is, however, more complex when the agent interacts with other agents that have potentially different capabilities and goals. The single-agent case is structurally different from the multi-agent case due to the added dimension of dynamic interactions between the adaptive agents. Multi-agent learning, i.e., the ability of the agents to learn how to cooperate and compete, becomes crucial in many domains. Autonomous agents and multi-agent systems (AAMAS) is an emerging multi-disciplinary area encompassing computer science, software engineering, biology, as well as cognitive and social sciences. A t- oretical framework, in which rationality of learning and interacting agents can be - derstood, is still under development in MASs, although there have been promising ?rst results. Soft cover.
Learning and Adaption in Multi-Agent Systems (2005)
ISBN: 9783540330592 bzw. 3540330593, vermutlich in Englisch, Springer Nature, neu, E-Book, elektronischer Download.
This book contains selected and revised papers of the International Workshop on Lea- ing and Adaptation in Multi-Agent Systems (LAMAS 2005), held at the AAMAS 2005 Conference in Utrecht, The Netherlands, July 26. An important aspect in multi-agent systems (MASs) is that the environment evolves over time, not only due to external environmental changes but also due to agent int- actions. For this reason it is important that an agent can learn, based on experience, and adapt its knowledge to make rational decisions and act in this changing environment autonomously. Machine learning techniques for single-agent frameworks are well established. Agents operate in uncertain environments and must be able to learn and act - tonomously. This task is, however, more complex when the agent interacts with other agents that have potentially different capabilities and goals. The single-agent case is structurally different from the multi-agent case due to the added dimension of dynamic interactions between the adaptive agents. Multi-agent learning, i.e., the ability of the agents to learn how to cooperate and compete, becomes crucial in many domains. Autonomous agents and multi-agent systems (AAMAS) is an emerging multi-disciplinary area encompassing computer science, software engineering, biology, as well as cognitive and social sciences. A t- oretical framework, in which rationality of learning and interacting agents can be - derstood, is still under development in MASs, although there have been promising ?rst results. eBook.
Learning and Adaption in Multi-Agent Systems (2005)
ISBN: 9783540330592 bzw. 3540330593, in Deutsch, Springer Shop, neu, E-Book, elektronischer Download.
This book contains selected and revised papers of the International Workshop on Lea- ing and Adaptation in Multi-Agent Systems (LAMAS 2005), held at the AAMAS 2005 Conference in Utrecht, The Netherlands, July 26. An important aspect in multi-agent systems (MASs) is that the environment evolves over time, not only due to external environmental changes but also due to agent int- actions. For this reason it is important that an agent can learn, based on experience, and adapt its knowledge to make rational decisions and act in this changing environment autonomously. Machine learning techniques for single-agent frameworks are well established. Agents operate in uncertain environments and must be able to learn and act - tonomously. This task is, however, more complex when the agent interacts with other agents that have potentially different capabilities and goals. The single-agent case is structurally different from the multi-agent case due to the added dimension of dynamic interactions between the adaptive agents. Multi-agent learning, i.e., the ability of the agents to learn how to cooperate and compete, becomes crucial in many domains. Autonomous agents and multi-agent systems (AAMAS) is an emerging multi-disciplinary area encompassing computer science, software engineering, biology, as well as cognitive and social sciences. A t- oretical framework, in which rationality of learning and interacting agents can be - derstood, is still under development in MASs, although there have been promising "rst results. eBook.
Learning and Adaption in Multi-Agent Systems - First International Workshop, LAMAS 2005, Utrecht, The Netherlands, July 25, 2005, Revised Selected Papers (2005)
ISBN: 9783540330592 bzw. 3540330593, in Deutsch, Springer Berlin Heidelberg, neu, E-Book, elektronischer Download.
Learning and Adaption in Multi-Agent Systems: This book contains selected and revised papers of the International Workshop on Lea- ing and Adaptation in Multi-Agent Systems (LAMAS 2005), held at the AAMAS 2005 Conference in Utrecht, The Netherlands, July 26. An important aspect in multi-agent systems (MASs) is that the environment evolves over time, not only due to external environmental changes but also due to agent int- actions. For this reason it is important that an agent can learn, based on experience, and adapt its knowledge to make rational decisions and act in this changing environment autonomously. Machine learning techniques for single-agent frameworks are well established. Agents operate in uncertain environments and must be able to learn and act - tonomously. This task is, however, more complex when the agent interacts with other agents that have potentially different capabilities and goals. The single-agent case is structurally different from the multi-agent case due to the added dimension of dynamic interactions between the adaptive agents. Multi-agent learning, i.e., the ability of the agents to learn how to cooperate and compete, becomes crucial in many domains. Autonomous agents and multi-agent systems (AAMAS) is an emerging multi-disciplinary area encompassing computer science, software engineering, biology, as well as cognitive and social sciences. A t- oretical framework, in which rationality of learning and interacting agents can be - derstood, is still under development in MASs, although there have been promising rst results. Englisch, Ebook.
Learning and Adaption in Multi-Agent Systems : First International Workshop, Lamas 2005, Utrecht, the Netherlands, July 25, 2005, Revised Selected Papers (2006)
ISBN: 9783540330530 bzw. 3540330534, vermutlich in Englisch, Springer-Verlag Gmbh Apr 2006, Taschenbuch, neu.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
Neuware - This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Learning and Adaption in Multi-Agent Systems, LAMAS 2005, held in The Netherlands, in July 2005, as an associated event of AAMAS 2005. The 13 revised papers presented together with two invited talks were carefully reviewed and selected from the lectures given at the workshop. 235 pp. Englisch, Books.
Learning and Adaption in Multi-Agent Systems (2006)
ISBN: 9783540330530 bzw. 3540330534, in Deutsch, Springer-Verlag Gmbh Apr 2006, Taschenbuch, neu.
Neuware - This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Learning and Adaption in Multi-Agent Systems, LAMAS 2005, held in The Netherlands, in July 2005, as an associated event of AAMAS 2005. The 13 revised papers presented together with two invited talks were carefully reviewed and selected from the lectures given at the workshop. 235 pp. Englisch.
Learning and Adaption in Multi-Agent Systems : First International Workshop, LAMAS 2005, Utrecht, the Netherlands, July 25, 2005, Revised Selected Papers (2006)
ISBN: 9783540330530 bzw. 3540330534, vermutlich in Englisch, Springer, Taschenbuch, gebraucht, akzeptabler Zustand, Erstausgabe.
Former library book; may include library markings. Used book that is in clean, average condition without any missing pages. Books.
Learning and Adaption in Multi-Agent Systems (2005)
ISBN: 9783540330592 bzw. 3540330593, in Deutsch, Springer Berlin Heidelberg, Taschenbuch, neu.
Learning and Adaption in Multi-Agent Systems: First International Workshop, LAMAS 2005, Utrecht, The Netherlands, July 25, 2005, Revised Selected . / Lecture Notes in Artificial Intelligence) (2006)
ISBN: 9783540330530 bzw. 3540330534, vermutlich in Englisch, Springer, Taschenbuch, gebraucht, guter Zustand.
Von Händler/Antiquariat, GuthrieBooks.
Springer, 2006-04-10. Paperback. Very Good. Ex-library paperback in very nice condition with the usual markings and attachments.
Learning and Adaption in Multi-Agent Systems: First International Workshop, LAMAS 2005, Utrecht, The Netherlands, July 25, 2005, Revised Selected Papers (Lecture Notes in Computer Science) (2006)
ISBN: 9783540330530 bzw. 3540330534, in Deutsch, Springer, Berlin/Heidelberg, Deutschland, Taschenbuch, neu, Erstausgabe.
1st edition. 217 pages. 9.25x6.25x0.50 inches. In Stock.