By Janneke H. Bolt (auth.), Roberto Serra, Rita Cucchiara (eds.)
This e-book constitutes the refereed court cases of the eleventh overseas convention of the Italian organization for synthetic Intelligence, AI*IA 2009, held in Reggio Emilia, Italy, in December 2009.
The 50 revised complete papers awarded including three invited talks have been rigorously reviewed and chosen from eighty three submissions. The papers are prepared in topical sections on wisdom illustration and reasoning, computing device studying, evolutionary computation, seek, average language processing, multi-agent structures and application.
Read Online or Download AI*IA 2009: Emergent Perspectives in Artificial Intelligence: XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia, Italy, December 9-12, 2009 Proceedings PDF
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Extra resources for AI*IA 2009: Emergent Perspectives in Artificial Intelligence: XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia, Italy, December 9-12, 2009 Proceedings
Dl+log: Tight Integration of Description Logics and Disjunctive Datalog. In: Proc. KR 2006, pp. 68–78. AAAI Press, Menlo Park (2006) 12. : Artiﬁcial Intelligence: a Modern Approach. Prentice-Hall, Englewood Cliﬀs (2002) 13. : Introduction to Knowledge Systems. org/ Hard QBF Encodings Made Easy: Dream or Reality? it Abstract. In a recent work we have shown that quantified treewidth is an effective empirical hardness marker for quantified Boolean formulas (QBFs), and that a preprocessor geared towards decreasing quantified treewidth is a potential enabler for the solution of hard QBF encodings.
Pulina and A. 0 is more effective than Q U BIS. Finally, we study the impact of preprocessing with respect to several QBF encodings and considering the overall performances of several state-of-the-art QBF solvers. 0 is always at least as effective as Q U BIS and, for specific combinations of solvers/encodings, it can decrease the hardness of the encodings. 0 and other state-of-the-art preprocessors can be explained by a change in some structural parameters of the formulas after preprocessing. 0 and other state-of-the-art preprocessors do not improve substantially on our ability to solve difficult encodings, so that making hard encodings easier remains confined to specific cases only.
Artif. Intell. 19(1), 17–37 (1982) 8. : Combining Horn Rules and Description Logics in Carin. Artif. Intell. 104(1-2), 165–209 (1998) 9. : Development and Application of a Metric on Semantic Nets. IEEE Trans SMC 19, 17–30 (1989) 10. : Using Information Content to Evaluate Semantic Similarity in a Taxonomy. In: XIth IJCAI, pp. 448–453 (1995) 11. : Dl+log: Tight Integration of Description Logics and Disjunctive Datalog. In: Proc. KR 2006, pp. 68–78. AAAI Press, Menlo Park (2006) 12. : Artiﬁcial Intelligence: a Modern Approach.
AI*IA 2009: Emergent Perspectives in Artificial Intelligence: XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia, Italy, December 9-12, 2009 Proceedings by Janneke H. Bolt (auth.), Roberto Serra, Rita Cucchiara (eds.)