Titlebook: Computational Intelligence in Games; Norio Baba,Lakhmi C. Jain Book 2001 Springer-Verlag Berlin Heidelberg 2001 algorithms.computational i

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Adam Sobanski Dr.,Jens Hollmanntise in the form of features that are believed to be important to playing well. In particular, we have focused on the use of a population of neural networks, where each network serves as an evaluation function to describe the quality of the current board position. After only a little more than 800 g

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Jens Hollmann,Adam Sobanski Dr.at make position evaluation extremely difficult. Development of conventional Go programs is hampered by their knowledge-intensive nature. We demonstrate a viable alternative by training neural networks to evaluate Go positions via temporal difference (TD) learning.

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https://doi.org/10.1007/978-3-8349-8591-0markets (e.g., five markets). Our market selection game is a non-cooperative repeated game where every player is supposed to simultaneously choose a single market for maximizing its own payoff obtained by selling its product at the selected market. It is assumed that the market price of the product

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Norio Baba,Lakhmi C. JainPresentation of state-of-the-art concepts and most recent research on the application of computational intelligence techniques in games.Including a new approach of evolving a neural network to play ch

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