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Titlebook: KI-97: Advances in Artificial Intelligence; 21st Annual German C Gerhard Brewka,Christopher Habel,Bernhard Nebel Conference proceedings 199

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樓主: Optician
31#
發(fā)表于 2025-3-26 21:45:43 | 只看該作者
Defining decision rules in signed horn clauses,his paper we define some well-known, rather simple rules from decision theory within a framework of many-valued logic programming. We show how these rules can also be generalized using partially ordered preference functions and how they can apply to multi-agent systems.
32#
發(fā)表于 2025-3-27 02:38:20 | 只看該作者
Conference proceedings 1997eptember 1997..The volume presents revised versions of 26 full papers and 10 posters selected from around 70 submissions from more than 15 countries. Also included are three excellent invited contributions by Anthony G. Cohn, Kurt Konolige, and Pat Langley. The papers are organized in topical sectio
33#
發(fā)表于 2025-3-27 08:29:33 | 只看該作者
34#
發(fā)表于 2025-3-27 11:26:57 | 只看該作者
Causation and nonmonotonic temporal reasoning, approaches, namely Baker‘s account and ‘chronological minimization with filter preferential entailment’, can be reinterpreted as approximations of Io. We thus provide a reinterpretation in terms of causal network theory of much of the work done in nonmonotonic temporal reasoning.
35#
發(fā)表于 2025-3-27 17:13:27 | 只看該作者
36#
發(fā)表于 2025-3-27 18:10:38 | 只看該作者
Minimal model generation based on E-hyper tableaux,e employed to obtain minimal models. This may be a great factor of inefficiency. In this paper we develop an approach to generate the minimal models, without explicit minimization process, based on E-hyper tableau which is a variant of hyper tableaux. The soundness and completeness of the procedure is shonw.
37#
發(fā)表于 2025-3-27 23:49:34 | 只看該作者
38#
發(fā)表于 2025-3-28 04:31:25 | 只看該作者
Rigid hypertableaux,I have implemented and evaluated a proof procedure which takes advantage of proof confluence and addresses the fairness problem of tableau caluli with a redundancy criterion based upon literal subsumption.
39#
發(fā)表于 2025-3-28 07:03:24 | 只看該作者
40#
發(fā)表于 2025-3-28 11:14:23 | 只看該作者
Machine learning for adaptive user interfaces,tinguish them from more traditional applications. After 1655 06 this, we consider some examples of adaptive interfaces that use inductive methods to personalize their behavior, and we report some ongoing research that extends these ideas in the automobile environment.
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