Evolving an expert checkers playing program without using humanexpertise
IEEE Transactions on Evolutionary Computation
Observing the evolution of neural networks learning to play the game of Othello
IEEE Transactions on Evolutionary Computation
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IEEE WCCI 2008 also saw the latest instalment of the Neural Network Othello competition. The aim of this is to find the best performing neural network (or more generally, any form of value function) for playing Othello. The mode of operation is as follows. Entrants submit their trained architectures to the competition web server, which evaluates them against a standard heuristic player, and immediately updates a league table with the performance of the submitted player. The leading entry by each entrant is then played off in a round robin league against the other leading entries to determine the competition winner. The competition server has been running for over two years now, and has received well over 1,000 entries. The IEEE CEC 2006 entry was won by an MLP (with a single hidden layer), submitted by Kyung-Joong Kim and Sung-Bae Cho of Yonsei University, Seoul, South Korea. In the league table below this entry is referred to as CEC 2006 Champ.