Advances in Artificial Intelligence: 21st Conference of the by Rocío Alaiz-Rodríguez (auth.), Sabine Bergler (eds.)

By Rocío Alaiz-Rodríguez (auth.), Sabine Bergler (eds.)

This ebook constitutes the refereed court cases of the twenty first convention of the Canadian Society for Computational experiences of Intelligence, Canadian AI 2008, held in Windsor, Canada, in may perhaps 2008.

The 30 revised complete papers provided including five revised brief papers have been conscientiously reviewed and chosen from seventy five submissions. The papers current unique fine quality study in all components of synthetic Intelligence and follow ancient AI ideas to trendy challenge domain names in addition to fresh concepts to old challenge settings.

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Advances in Artificial Intelligence: 21st Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2008 Windsor, Canada, May 28-30, 2008 Proceedings

This booklet constitutes the refereed court cases of the twenty first convention of the Canadian Society for Computational stories of Intelligence, Canadian AI 2008, held in Windsor, Canada, in may perhaps 2008. The 30 revised complete papers provided including five revised brief papers have been rigorously reviewed and chosen from seventy five submissions.

Extra info for Advances in Artificial Intelligence: 21st Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2008 Windsor, Canada, May 28-30, 2008 Proceedings

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N }. Then: Δd,max (Γ ) = mod(Γ ) if mod(Γ ) = ∅, Λ otherwise. Proof. If mod(Γ ) = ∅, then Δd,f (Γ ) = mod(Γ ) for every d and f (see [2]). Otherwise, there is at least on element in Γ that is not satisfiable, and so, for every valuation μ ∈ Λ, δd,max (μ, Γ ) = max{d(μ, ψ1 ), . . , d(μ, ψn )} = kd . It follows, then, that in this case Δd,max (Γ ) = Λ. Proposition 4 implies that for describing reasoning with uniform distances under the minmax strategy, it is enough to examine the drastic distance (and so henceforth we focus only on dU ): Corollary 2.

M Proof. Immediately follows from Proposition 11. m Some Simplified Forms of Reasoning with Distance-Based Entailments 5 45 Summation of Distances Summation of distances is probably the most common approach for distancebased reasoning. In this section we consider this kind of reasoning. Again, we first consider the general case and then concentrate on more specific distances. 1 Arbitrary Pseudo Distances Consider the system SΣ in Figure 4.

By simultaneously increasing the number of words in the dictionary, applying a stemming algorithm, and assigning a weight to each dictionary word, we substantially increased the size of the dictionary. The proportion of positive and negative token matches did not change, and we hypothesize that for each positive match that was found, it was equally likely to find a negative match, thereby creating a neutral net effect. Given these results, it appears that the selection of words that are included in the dictionary is very important for the lexical approach.

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