Download Intelligent Agents and Multi-Agent Systems: 5th Pacific Rim by Guido Boella, Rossana Damiano (auth.), Kazuhiro Kuwabara, PDF

By Guido Boella, Rossana Damiano (auth.), Kazuhiro Kuwabara, Jaeho Lee (eds.)

Autonomous brokers and multi-agent structures are computational platforms during which a number of (semi-)autonomous brokers have interaction with one another or interact to accomplish a few set of initiatives or fulfill a few set of objectives. those platforms may possibly contain computational brokers which are homogeneous or heterogeneous, they might contain actions at the a part of brokers having universal or detailed ambitions, and so they may well contain participation at the a part of people and clever brokers. This quantity comprises chosen papers from PRIMA 2002, the fifth Paci?c Rim overseas Workshop on Multi-Agents, held in Tokyo, Japan, on August 18–19, 2002 along side the seventh Paci?c Rim foreign convention on Arti?cial Intelligence (PRICAI-02). PRIMA is a chain of workshops on - tonomous brokers and multi-agent structures, integrating actions within the Asian and Paci?c Rim international locations. PRIMA 2002 outfitted at the nice good fortune of its pre- cessors, PRIMA’98 in Singapore, PRIMA’99 in Kyoto, Japan, PRIMA 2000 in Melbourne, Australia, and PRIMA 2001 in Taipei, Taiwan. We got 35 submissions to this workshop from 10 nations. each one paper used to be reviewed through 3 across the world well known software committee individuals. After cautious experiences, 15 papers have been chosen for this quantity. we want to thank all of the authors who submitted papers to the workshop. we might additionally wish to thank the entire software committee contributors for his or her the best option paintings in reviewing the papers. eventually, we thank the editorial sta? of Springer-Verlag for publishing this quantity within the Lecture Notes in Arti?cial Intelligence.

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Extra resources for Intelligent Agents and Multi-Agent Systems: 5th Pacific Rim International Workshop on Multi-Agents, PRIMA 2002 Tokyo, Japan, August 18–19, 2002 Proceedings

Example text

However, they are not sufficient to resolve the above weak points, because they do not explicitly take into account the complex behavior caused by learning and interaction. To complement the weak points of multiagent systems, one of the authors has proposed a new framework, individual level analysis, in which analysts create statistics from agent activities and evaluate the validity of simulations or working multiagent systems using individual characteristics of agents[7]. Using this framework, we employed the concepts of action uncertainty[8] and dominant input attributes[9], which are based on information entropy and are defined in general terms.

5 shows H(t) with intervals of 250 steps, corresponding Fig. 6. It is possible to tell intuitively that Ma1 and Ma2 are different. To enable more precise discussion, we employed a Monte Carlo simulation. The result is shown in Table 3. As system level features, we calculated E{p(t)} and V {p(t)}, the mean and standard deviation of the stock price series, respectively, and the autocorrelation of p(t) with time lags τ = 100 and τ = 200. As an ¯ ¯ individual level feature, we calculated E{H(t)}, which is the mean of H(t).

Every cognition worker can be seen as a set of rules or a finite state machine implementing a layer, with the lower layers governing the basic behavior and the upper layers adding more sophisticated control behavior. If a cognition worker is free, it sends a request to the sensor administrator for new events. After receiving a reply message, the cognition worker maps the received event to a set of tasks, which are sent to the task administrator, and moves on to process other events, if any. The cognition workers determine the cognition level of an agent.

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