منابع مشابه
Learning to Play Othello with Deep Neural Networks
Achieving superhuman playing level by AlphaGo corroborated the capabilities of convolutional neural architectures (CNNs) for capturing complex spatial patterns. This result was to a great extent due to several analogies between Go board states and 2D images CNNs have been designed for, in particular translational invariance and a relatively large board. In this paper, we verify whether CNN-base...
متن کاملLearning to Play Othello with N -Tuple Systems
This paper investigates the use of n-tuple systems as position value functions for the game of Othello. The architecture is described, and then evaluated for use with temporal difference learning. Performance is compared with previously developed weighted piece counters and multi-layer perceptrons. The n-tuple system is able to defeat the best performing of these after just five hundred games o...
متن کاملReduction of the search space to find perfect play of 6×6 board Othello
In 1993, mathematician Feinstein found out perfect play on 6×6 board Othello gives 16-20 loss for the first player by using computer. He reported on the Web that it took two weeks to search forty billion positions in order to obtain the result. In our previous papers, we confirmed the perfect play he found is correct. And we also found another perfect play different from the one he found to sea...
متن کاملNeuro-Evolution Through Augmenting Topologies Applied To Evolving Neural Networks To Play Othello
Many different approaches to game playing have been suggested including alpha-beta search, temporal difference learning, genetic algorithms, and coevolution. Here, a powerful new algorithm for neuroevolution, Neuro-Evolution for Augmenting Topologies (NEAT), is adapted to the game playing domain. Evolution and coevolution were used to try and develop neural networks capable of defeating an alph...
متن کاملMachine Learning of Othello Heuristics
The machine learning algorithm of [3] is applied to the problem of learning which heuristics to apply when playing the board game Othello. The problem is large, for there are 46,875 heuristics considered. The results are respectable; the Learner is able to beat a practiced human player approximately fifty percent of the time. Suggestions for improvement are included.
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ژورنال
عنوان ژورنال: Cahiers Élisabéthains: A Journal of English Renaissance Studies
سال: 2019
ISSN: 0184-7678,2054-4715
DOI: 10.1177/0184767819826011e