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Discovering Complex Othello Strategies Through Evolutionary Neural Networks (1995)
David E. Moriarty
and
Risto Miikkulainen
An approach to develop new game playing strategies based on artificial evolution of neural networks is presented. Evolution was directed to discover strategies in Othello against a random-moving opponent and later against an alpha-beta search program. The networks discovered first a standard positional strategy, and subsequently a mobility strategy, an advanced strategy rarely seen outside of tournaments. The latter discovery demonstrates how evolutionary neural networks can develop novel solutions by turning an initial disadvantage into an advantage in a changed environment.
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Citation:
Connection Science
, Vol. 7 (1995), pp. 195--209.
Bibtex:
@article{moriarty:connsci95, title={Discovering Complex Othello Strategies Through Evolutionary Neural Networks}, author={David E. Moriarty and Risto Miikkulainen}, volume={7}, journal={Connection Science}, pages={195--209}, url="http://www.cs.utexas.edu/users/ai-lab?moriarty:connsci95", year={1995} }
People
Risto Miikkulainen
Faculty
risto [at] cs utexas edu
David E. Moriarty
Ph.D. Alumni
moriarty [at] alumni utexas net
Areas of Interest
Applications
Evolutionary Computation
Game Playing
Neuroevolution
Reinforcement Learning
Labs
Neural Networks