By Dov Gabbay (auth.), Michael Fisher, Leon van der Torre, Mehdi Dastani, Guido Governatori (eds.)

This e-book constitutes the court cases of the thirteenth overseas Workshop on Computational good judgment in Multi-Agent structures, CLIMA XIII, held in Montpellier, France, in August 2012. The eleven usual papers have been rigorously reviewed and chosen from 27 submissions and provided with 3 invited papers. the aim of the CLIMA workshops is to supply a discussion board for discussing innovations, according to computational common sense, for representing, programming and reasoning approximately brokers and multi-agent platforms in a proper way.

**Read Online or Download Computational Logic in Multi-Agent Systems: 13th International Workshop, CLIMA XIII, Montpellier, France, August 27-28, 2012. Proceedings PDF**

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This booklet constitutes the court cases of the thirteenth foreign Workshop on Computational good judgment in Multi-Agent platforms, CLIMA XIII, held in Montpellier, France, in August 2012. The eleven typical papers have been rigorously reviewed and chosen from 27 submissions and offered with 3 invited papers. the aim of the CLIMA workshops is to supply a discussion board for discussing innovations, in keeping with computational common sense, for representing, programming and reasoning approximately brokers and multi-agent structures in a proper approach.

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**Additional resources for Computational Logic in Multi-Agent Systems: 13th International Workshop, CLIMA XIII, Montpellier, France, August 27-28, 2012. Proceedings**

**Example text**

Note the following: 1. Common sense requires a solution of two extensions, either both x and z are in or both x and z are out. 2. the equational approach, as well as the situation in Figure 22, do give such two solutions: φ and {x, z}. The coalition approach of Caryol and Lagasquie-Schiex (Definition 5) give only one extension, namely {x, z}. Example 11. Consider Figure 23 x y z Fig. 23. Here, any two nodes support the third. The equations are as follows: x = 1 − max(1 − y, y − z) y = 1 − max(1 − x, 1 − z) z = 1 − max(1 − x, 1 − y) There are two solutions: x = y = z = 1 and x = y = z = 0.

P. Lam et al. To rectify these shortcomings, in this paper, we propose a totally distributed approach for ambient intelligence through Distributed Defeasible Speculative Reasoning (DDSR). We model an ambient environment as a Multi-Context System [3,4,5] and ambient agents as autonomous logic-based entities. Knowledge possessed by an agent is formalized as a local context theory and associations between the knowledge possessed by other ambient agents using askable literals. Inconsistencies and ambiguities in local context theory are handled by the semantics of Defeasible Logic (DL); while uncertainties or missing context information, on the other hand, will first be substituted by the default values used in the speculative computation process [6] and will be replaced by the “real” information when they are available.

Abstract dialectical frameworks. In: Proc. of the 20th International Conference on the Principles of Knowledge Representation and Reasoning (KR 2010), pp. 102–111 (2010) 24. : Integrating object and meta-level value based argumentation. , Hunter, A. ) COMMA. Frontiers in Artificial Intelligence and Applications, vol. 172, pp. 240–251. IOS Press (2008) 25. : Meta-Logical Investigations in Argumentation Networks. Research Monograph. de Abstract. Levesque introduced the notion of only-knowing to precisely capture the beliefs of a knowledge base.