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Titlebook: Engineering of Intelligent Systems; 14th International C László Monostori,József Váncza,Moonis Ali Conference proceedings 2001 Springer-Ver

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László Monostori,József Váncza,Moonis AliIncludes supplementary material:
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/e/image/311036.jpg
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https://doi.org/10.1057/9780230370555X-W-SAT. It is a population-based meta-heuristic founded on a formulation proposed two decades ago by Fred Glover. It uses linear combination on a population subset to create new solutions while other evolutionary approaches like genetic algorithms resort to randomization..First we propose a scatter
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https://doi.org/10.1007/978-3-030-54693-9orks to estimate the likelihood of a move being the best in a certain position. The moves considered more likely to be the best are examined first. We selected Lines of Action as a testing ground. We investigated several schemes to encode the moves in a neural net- work. In the experiments, the best
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https://doi.org/10.1007/978-1-137-57529-6ased on “items” is described. Items contain two classes of constraints that apply equally to knowledge and to data. Items are compared to an if-then, or rule-based, knowledge representation. Simple chunks of knowledge that can only be represented by a number of rules are represented as single items.
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The German Communists and the Rise of Nazism paper we propose different intuitions standing behind knowledge base update. Roughly speaking, we consider an update formula α not as an effect of an action to be performed, but rather as an observation about dynamically changing world made by an agent. This observation, if it is consistent with th
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https://doi.org/10.1007/978-3-642-99217-9and handling information conflict in updates. We then focus on the computational aspect of this approach. We show that under our framework, the model checking in an update is co-NP-complete, while the associated inference problem is . . . -complete. From a practical viewpoint, we propose two strateg
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