Download Artificial intelligence: methodology, systems and by Daniel Dochev, Paolo Traverso, Marco Pistore PDF

By Daniel Dochev, Paolo Traverso, Marco Pistore

This publication constitutes the refereed complaints of the thirteenth foreign convention on synthetic Intelligence: method, platforms, and purposes, AIMSA 2008, held in Varna, Bulgaria in September 2008.

The 30 revised complete papers offered including the ten posters have been rigorously reviewed and chosen from 109 submissions. The papers are prepared in topical sections on brokers; traditional language processing and textual content research; computer studying and data retrieval; wisdom illustration and reasoning; constraints, heuristics and seek; functions; posters.

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Artificial intelligence: methodology, systems and applications

This e-book constitutes the refereed court cases of the thirteenth foreign convention on synthetic Intelligence: technique, structures, and purposes, AIMSA 2008, held in Varna, Bulgaria in September 2008. The 30 revised complete papers offered including the ten posters have been rigorously reviewed and chosen from 109 submissions.

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They are based on an activity-chart that is a hierarchical data-flow diagram, where the functional capabilities of the 38 N. Spanoudakis and P. Moraitis Capabilities handle dangerous situation Activities determine user condition invoke heart rate service Functionalities algorithm invoke OSGi service get user coordinates service user present information to the user get user order get user preferences learn user habits request for services communicate Legend: update user preferences Human-Machine Interface (HMI) MIDP record technology learn user preference machine learning search broker JADE FIPA DF send message receive message JADE FIPA AMS Fig.

Considering these two assumptions only, we get what we call intrinsic relevance5 . According to this kind of relevance, any piece of information which contributes to information need of the agent is relevant. Even false information can be relevant, which is questionable in the context of multi-agent systems. If we add that a relevant information has to be true, then we get what we call contingent relevance. The term “contingent” is justified by the fact that this notion of relevance here highly depends on the current situation.

Thus, b can believe that an information is relevant for another agent a concerning Q, only if b knows about a’s information needs. Moreover, it can happen that b thinks that an information is relevant for a concerning an information need while it is not. e when b believes that a has an information need and a does not have this information need, or when b believes that ϕ is true and ϕ is not, or when b believes that a, from his beliefs and from ϕ, can deduce Q or (exclusive) deduce ¬Q and a does not have enough knowledge.

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