Advances in Artificial Intelligence: 24th Canadian by Eric Aaron, Juan Pablo Mendoza (auth.), Cory Butz, Pawan

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By Eric Aaron, Juan Pablo Mendoza (auth.), Cory Butz, Pawan Lingras (eds.)

This booklet constitutes the refereed complaints of the twenty fourth convention on synthetic Intelligence, Canadian AI 2011, held in St. John’s, Canada, in may possibly 2011. The 23 revised complete papers awarded including 22 revised brief papers and five papers from the graduate scholar symposium have been rigorously reviewed and chosen from eighty one submissions. The papers conceal a wide diversity of subject matters featuring unique paintings in all components of man-made intelligence, both theoretical or applied.

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Extra resources for Advances in Artificial Intelligence: 24th Canadian Conference on Artificial Intelligence, Canadian AI 2011, St. John’s, Canada, May 25-27, 2011. Proceedings

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Efficient haplotype inference with boolean satisfiability. In: AAAI. AAAI Press, Menlo Park (2006) 8. : Effective compilation of constraint models (2010) 9. : MiniZinc: Towards a standard CP modelling language. In: Bessi`ere, C. ) CP 2007. LNCS, vol. 4741, pp. 529–543. Springer, Heidelberg (2007) 10. cs. html 11. : Finite domain and symbolic inference methods for extensions of first-order logic. AI Communications (2010) (accepted) 12. : Cardinality Networks and Their Applications. In: Kullmann, O.

In this approach, systems with a high-level language helps users a lot and reduces the amount of expertise a user need to have, and thus provides a way of solving computationally hard AI problems to a wider variety of users. In this paper, we described how we extended our engine to handle complex terms. Having access to aggregates and arithmetic operators eases the task of describing problems for our system and, enables more users to work with our system for solving their theoretical and real-world problems.

Essentially, the syntax of IDP is very similar to that our system but their approach to ground a given specification is different. A ground formula is created using a top-down procedure. The formula is written in Term Normal Form, TNF, in which all arguments to predicates are variables and the complex terms can only appear in the atomic formula in the form x{≤, <, =, >, ≥}t(¯ y). And then, the atomic formulas which have complex terms are rewritten as disjunction or conjunction of atomic formulas in form x < t(¯ y ) and x > t(¯ y ) [11].

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