Titlebook: Computational Logic in Multi-Agent Systems; 4th International Wo Jürgen Dix,João Leite Conference proceedings 2005 Springer-Verlag Berlin H

毁坏

(Dis)Belief Change Based on Messages Processingrators when agents have to process messages about a static world. We propose to consider agents’ belief state as a set of pairs 〈belief, origin of the belief〉 combined with a preference relation over the agents embedded in the multi-agent system. The belief revision procedure for handling received m

优雅

Learning in BDI Multi-agent Systemsespite the relevance of the BDI model of rational agency, little work has been done to deal with its two main limitations: i) The lack of learning competences; and ii) The lack of explicit multi-agent functionality. From the multi-agent learning perspective, we propose a BDI agent architecture exten

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The Apriori Stochastic Dependency Detection (ASDD) Algorithm for Learning Stochastic Logic RulesD is based on features of the Apriori algorithm for mining association rules in large databases of sales transactions [1] and the MSDD algorithm for discovering stochastic dependencies in multiple streams of data [15]. Once these rules have been acquired the . algorithm assigns operator precedence w

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欢乐东方

某人

https://doi.org/10.1007/978-3-0348-6925-6 plans are successfully executable. Our implementation enables multiple agents executed as parallel functions in a single Lisp image. In addition, our approach maintains consistency between learning and the theory of practical reasoning.

ULCER

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Programming Groups of Rational Agentsth such formalism as a basis, we consider the grouping aspects within multi-agent systems. In particular, we describe how this logic-based approach to grouping has been implemented in . and consider how this language can be used for developing multi-agent systems.