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Titlebook: KI 2014: Advances in Artificial Intelligence; 37th Annual German C Carsten Lutz,Michael Thielscher Conference proceedings 2014 Springer Int

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51#
發(fā)表于 2025-3-30 08:22:31 | 只看該作者
A More Compact Translation of Pseudo-Boolean Constraints into CNF Such That Generalized Arc Consiste way and we present a concrete instantiation, resulting in a space complexity of . clauses in contrast to . clauses generated by the previously best known encoding that maintains generalized arc consistency.
52#
發(fā)表于 2025-3-30 15:20:01 | 只看該作者
Reasoning in ${mathcal{ALC}}$ with Fuzzy Concrete Domainsility can be regained. Typically, the concrete domain predicates are crisp, which is a limitation for some applications. In this paper we investigate crisp . in combination with fuzzy concrete domains for general TBoxes, devise conditions for decidability, and give a tableau-based reasoning algorithm.
53#
發(fā)表于 2025-3-30 17:52:42 | 只看該作者
Conference proceedings 2014ers are organized in thematic topics on cognitive modeling, computer vision, constraint satisfaction, search, and optimization, knowledge representation and reasoning, machine learning and data mining, planning and scheduling..
54#
發(fā)表于 2025-3-31 00:02:54 | 只看該作者
0302-9743 s. The papers are organized in thematic topics on cognitive modeling, computer vision, constraint satisfaction, search, and optimization, knowledge representation and reasoning, machine learning and data mining, planning and scheduling..978-3-319-11205-3978-3-319-11206-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
55#
發(fā)表于 2025-3-31 04:00:56 | 只看該作者
56#
發(fā)表于 2025-3-31 08:56:12 | 只看該作者
57#
發(fā)表于 2025-3-31 09:53:08 | 只看該作者
A Note on Chances and Limitations of Psychometric AIrly investigate HAI and how to proceed after the very first steps of implementing an HAI system; etc. In this note I assess the ways in which the approach of Psychometric Artificial Intelligence [1] can (and cannot) be taken as a foundation for a scientific approach to HAI.
58#
發(fā)表于 2025-3-31 16:05:48 | 只看該作者
59#
發(fā)表于 2025-3-31 19:25:36 | 只看該作者
CDCL Solver Additions: Local Look-Ahead, All-Unit-UIP Learning and On-the-Fly Probinghat are hard to find by unit propagation and clause learning alone. With the additional reasoning steps of these techniques the resulting algorithm is able to solve SAT formulas that cannot be solved by the original algorithm.
60#
發(fā)表于 2025-4-1 00:11:40 | 只看該作者
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