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Titlebook: Artificial Intelligence: Methodology, Systems, and Applications; 10th International C Donia Scott Conference proceedings 2002 Springer-Verl

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發(fā)表于 2025-3-26 23:52:01 | 只看該作者
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發(fā)表于 2025-3-27 04:52:26 | 只看該作者
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發(fā)表于 2025-3-27 06:33:26 | 只看該作者
A Replanning Algorithm for a Reactive Agent Architecture,ithm we propose exploits the planner’s ability to provide an approximate evaluation of partial plans: it starts from a fully refined plan and makes it more partial until it finds a more partial plan which subsumes more promising refinements; at that point, the planning process is restarted from the current partial plan.
34#
發(fā)表于 2025-3-27 09:31:52 | 只看該作者
Multimodal Speech Synthesis: Improving Information Flow in Dialogue Systems Using 3D Talking Heads,alogue systems. Our motivation for moving into audiovisual output is to investigate the advantages of multimodality in human-system communication. While the mainstream character animation area has focused on the naturalness and realism of the animated agents, our primary concern has been the possibl
35#
發(fā)表于 2025-3-27 16:57:10 | 只看該作者
Efficient Relational Learning from Sparse Data,d. It aims at building an easy-to-use relational learner and it focuses on the tasks that are solvable with the tool. Assumptionbased learning, the new learning paradigm is introduced and the ABL system . is described. A methodology for experimental evaluation of ILP systems is introduced and experi
36#
發(fā)表于 2025-3-27 19:15:53 | 只看該作者
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發(fā)表于 2025-3-27 22:49:22 | 只看該作者
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39#
發(fā)表于 2025-3-28 06:28:13 | 只看該作者
Using Failed Local Search for SAT as an Oracle for Tackling Harder A.I. Problems More Efficiently,igence domain. In this paper, it is shown that a smart use of the computation of a local search that . to solve a NP-hard decision problem . can sometimes slash down the computing time for the resolution of computationally . optimization problems containing . as a sub-problem. As a case study, we ta
40#
發(fā)表于 2025-3-28 11:09:31 | 只看該作者
A Heuristic for Planning Based on Action Evaluation,he cost of applying each action of the domain by performing a forward search in a relaxed version of the initial problem. The estimates for the actions are then utilized in a backward search on the original problem. The heuristic, which has been further refined by a fact ordering and several domain-
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