Languages, Methodologies and Development Tools for by Dave Robertson, Fausto Giunchiglia, Frank van Harmelen,

By Dave Robertson, Fausto Giunchiglia, Frank van Harmelen, Maurizio Marchese, Marta Sabou (auth.), Mehdi Dastani, Amal El Fallah Seghrouchni, João Leite, Paolo Torroni (eds.)

This booklet constitutes the completely refereed post-workshop lawsuits of the 1st foreign Workshop on Languages, Methodologies and improvement instruments for Multi-Agent structures, LADS 2007, held in Durham, united kingdom, in September 2007. The workshop used to be a part of MALLOW 2007, a federation of workshops on Multi-Agent Logics, Languages, and Organizations.

The 15 revised complete papers, provided including 1 invited paper reporting the goals and achievements of the OpenKnowledge venture, have been rigorously reviewed and chosen from 32 submissions. The papers are geared up in topical sections on agent reasoning and semantics, declarative languages and applied sciences, methodologies and layout, and improvement frameworks.

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Languages, Methodologies and Development Tools for Multi-Agent Systems: First International Workshop, LADS 2007, Durham, UK, September 4-6, 2007. Revised Selected Papers

This publication constitutes the completely refereed post-workshop lawsuits of the 1st overseas Workshop on Languages, Methodologies and improvement instruments for Multi-Agent platforms, LADS 2007, held in Durham, united kingdom, in September 2007. The workshop was once a part of MALLOW 2007, a federation of workshops on Multi-Agent Logics, Languages, and companies.

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Additional resources for Languages, Methodologies and Development Tools for Multi-Agent Systems: First International Workshop, LADS 2007, Durham, UK, September 4-6, 2007. Revised Selected Papers

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However, the preference information required to determine the success of an attack is often assumed pre-specified as a given ordering, and external to the logical formalism. This does not account for the fact that preferences may vary according to context, and because information sources (be they agents or otherwise) may disagree as to the criteria by which the strengths of arguments should be valuated, or the valuations assigned for a given criterion. Hence, to facilitate agent flexibility and adaptability, requires argumentation based reasoning about, as well as with, defeasible and possibly conflicting preference information.

4 Integrating Logic and Probability This section provides an overview of our approach to integrating logic and probability. The key idea is to allow densities to appear in theories. For this reason, we first set up some logical machinery for this. In the logic, we let Density σ denote Probabilistic and Logical Beliefs 25 the type of densities whose arguments have type σ. Any term of type Density σ, for some σ, is called a density. We also make available the functions from Section 3 that compose functions whose codomains are densities.

The functions setOfBalls and ballsDrawn are defined informally above; formal recursive definitions can be given. Marginalisations and conditionalisations of the given density can be computed to obtain answers to different questions. For example, the following gives the probability that the number of balls in the urn is m after the colours [o1 , o2 , . . , od ] from d draws have been observed: 1 K (joint d (m, s, l, [o1 , o2 , . . , od ])), s l where K is a normalisation constant, s ranges over { s | (setOfBalls m s) > 0 }, and l ranges over { l | (ballsDrawn d s l) > 0 }.

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