Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Feature-based methods for large scale dynamic programming
Machine Learning - Special issue on reinforcement learning
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Genetically optimizing the speed of programs evolved to play tetris
Advances in genetic programming
Neuro-Dynamic Programming
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Learning tetris using the noisy cross-entropy method
Neural Computation
Benchmarking a BI-population CMA-ES on the BBOB-2009 function testbed
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Tetris is hard, even to approximate
COCOON'03 Proceedings of the 9th annual international conference on Computing and combinatorics
Designing artificial tetris players with evolution strategies and racing
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Reducing the learning time of tetris in evolution strategies
EA'11 Proceedings of the 10th international conference on Artificial Evolution
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In the paper, we focus the use of evolutionary algorithms to learn strategies to play the game of Tetris. We describe the problem and discuss the nature of the search space. We present experiments to illustrate the learning process of our artificial player, and provide a new procedure to speed up the learning time. The results we present compare with the best known artificial player, and show how our evolutionary algorithm is able to rediscover player strategies previously published. Finally we provide some ideas to improve the performance of artificial Tetris players.