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Titlebook: Knowledge-Free and Learning-Based Methods in Intelligent Game Playing; Jacek Mańdziuk Book 2010 Springer-Verlag Berlin Heidelberg 2010 art

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Evaluation Function Learningograms both aspects are painstakingly addressed and both highly contribute to the final program’s rating. In the CI motivated approaches the focus is much more on the evaluation function aspect rather than the search, since the latter - in its technical implementation - is located outside the scope of CI.
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1860-949X ent in their approaches to game pl- ing. Humans use intuition, perception mechanisms, selective search, creat- ity, abstraction, heuristic abilities and other cognitive skills to compensate their (comparably) slow information processing speed, relatively low m- ory capacity, and limited search abili
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Game RepresentationThese features are often reflected in the form of 2D patterns, rather than linear vectors. Intuitively, when talking about efficient game representations, the ones accounting for spatial, two-dimensional relations should also deserve attention.
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Efficient TD Trainingature one might suppose that all relevant questions concerning this type of learning have already been answered and if there exist any ambiguities they must refer to secondary issues or specific implementation details.
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Move Ranking and Search-Free Playingr exploration of the most promising paths. Certainly in competitive tournament play, due to time constraints, efficient move pre-ordering must be either implemented in a search-free way or rely on shallow search in order to devote the remaining time to deeper, selective search.
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Creativity and Knowledge Discoverynovel combination of old ideas,” where the novelty of a creative solution is reflected by its nonobviousness and interestingness. Yet another dictionary definition is “to bring into being or form out of nothing.”
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