Adaptive Agents and Multi-Agent Systems II: Adaptation and - download pdf or read online

By Jürgen Schmidhuber (auth.), Daniel Kudenko, Dimitar Kazakov, Eduardo Alonso (eds.)

ISBN-10: 3540252606

ISBN-13: 9783540252603

Adaptive brokers and multi-agent platforms is an rising and interesting interdisciplinary region of analysis and improvement related to synthetic intelligence, software program engineering, and developmental biology, in addition to cognitive and social science.

This e-book provides 17 revised and thoroughly reviewed papers taken from workshops at the subject in addition to 2 invited papers through top researchers within the zone. The papers take care of numerous facets of computer studying, model, and evolution within the context of agent structures and self reliant agents.

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By Jürgen Schmidhuber (auth.), Daniel Kudenko, Dimitar Kazakov, Eduardo Alonso (eds.)

ISBN-10: 3540252606

ISBN-13: 9783540252603

Adaptive brokers and multi-agent platforms is an rising and interesting interdisciplinary region of analysis and improvement related to synthetic intelligence, software program engineering, and developmental biology, in addition to cognitive and social science.

This e-book provides 17 revised and thoroughly reviewed papers taken from workshops at the subject in addition to 2 invited papers through top researchers within the zone. The papers take care of numerous facets of computer studying, model, and evolution within the context of agent structures and self reliant agents.

Show description

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Extra info for Adaptive Agents and Multi-Agent Systems II: Adaptation and Multi-Agent Learning

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As in the “content” posts, the context in which each author resides defines his/her place in the network, and vice versa - the (identities of the) contributors to a subject become part of its context. Filters may be applied to the graph view, to project certain aspects of the Postext. The links that represent contribution maybe filtered on a temporal basis, or the nodes representing authors may be hidden altogether. The entire system can be searched, and a mechanism of personal bookmarks exists to facilitate navigation.

To this end, we have constructed an artificial-life environment in which a society of learning agents uses speech to direct others to resources vital to survival using the same underlying computational mechanism as they use to navigate. This differs from previous work in the field of simulating language evolution by viewing language as tool with a particular purpose rather than an abstract method of information coding. We discuss the altruistic nature of this activity and evaluate the benefits this brings to the community by measuring the difference in performance between populations of agents able to communicate and those unable to do so.

Postext (as other distributed structures) is reinstating freedom not only from scientific “dictatorships”, but also from the more recent forms of mainstream (minimal denominator) cultural totalitarianism. Most importantly, Postext is easily communicable to newcomers and can solve the problems of the modern educational systems. This is a big problem in the realm of “classic” text - even the most complete library is not self-explanatory (Poincare: “facts don’t speak”). Thus the increased penury in teachers capable to teach modern knowledge as it is being generated.

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Adaptive Agents and Multi-Agent Systems II: Adaptation and Multi-Agent Learning by Jürgen Schmidhuber (auth.), Daniel Kudenko, Dimitar Kazakov, Eduardo Alonso (eds.)


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