By Victor Lesser (auth.), Yang Xiang, Brahim Chaib-draa (eds.)

ISBN-10: 3540403000

ISBN-13: 9783540403005

This e-book constitutes the refereed lawsuits of the sixteenth convention of the Canadian Society for Computational reports of Intelligence, AI 2003, held in Halifax, Canada in June 2003.

The 30 revised complete papers and 24 revised brief papers awarded have been rigorously reviewed and chosen from 106 submissions. The papers are geared up in topical sections on wisdom illustration, seek, constraint pride, computer studying and knowledge mining, AI and net purposes, reasoning lower than uncertainty, brokers and multi-agent platforms, AI and bioinformatics, and AI and e-commerce.

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Extra info for Advances in Artificial Intelligence: 16th Conference of the Canadian Society for Computational Studies of Intelligence, AI 2003, Halifax, Canada, June 11–13, 2003, Proceedings

Example text

To r show that RB = 0 is not an actual cause of PH = 1, note that AB must be in W for condition C2 since its value must be changed to make PH = 0 for C2(a). BF lies on the r only path from RB to PH and must be in the set Z . Setting (RB, AB) = (1,1) makes PH = 0 ( ¬ϕ ) satisfying condition C2(a). However, condition C2(b) fails when the r subset {BF} of Z is returned to its original value (that is, PH = 0 ( ¬ϕ ) when BF = 0 and AB = 1). In the language of the NESS test, an actually sufficient set for which not repairing the brakes is a necessary condition includes the brakes being applied and the brakes failing.

The actor that is cast in the principal role is called the principal of the behavioral pattern. In fact the goal of a behavior pattern is to prescribe all of the potential actions of the principal. We say that the principal is bound to a behavioral pattern since an actor can only be the principal of one behavioral pattern at any one time. The actions of a behavioral pattern’s principal are completely determined by the behavioral pattern it is bound to. A principal stays bound to a behavioral pattern until it is unbound.

To our knowledge, however, answer formulation has not been investigated in the context of human-computer interaction (HCI) to generate answer sentences rather than exact answers only. In the following, we will discuss our experiments in answer formulation for extraction and for HCI purposes, and argue that improving the linguistic quality of formulations is beneficial for both purposes. 3 Formulation Templates Our first experiments with answer formulation were geared toward improving our results in answer extraction at the recent TREC-11 conference [15].

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Advances in Artificial Intelligence: 16th Conference of the Canadian Society for Computational Studies of Intelligence, AI 2003, Halifax, Canada, June 11–13, 2003, Proceedings by Victor Lesser (auth.), Yang Xiang, Brahim Chaib-draa (eds.)


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