Empirical methods for artificial intelligence
Empirical methods for artificial intelligence
Evolving neural networks through augmenting topologies
Evolutionary Computation
Tracking the Red Queen: Measurements of Adaptive Progress in Co-Evolutionary Simulations
Proceedings of the Third European Conference on Advances in Artificial Life
Continual Coevolution Through Complexification
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Efficient Reinforcement Learning Through Evolving Neural Network Topologies
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Solution concepts in coevolutionary algorithms
Solution concepts in coevolutionary algorithms
Ideal Evaluation from Coevolution
Evolutionary Computation
Efficient evolution of neural network topologies
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
New methods for competitive coevolution
Evolutionary Computation
Competitive coevolution through evolutionary complexification
Journal of Artificial Intelligence Research
Learning the ideal evaluation function
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
A game-theoretic memory mechanism for coevolution
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Real-time neuroevolution in the NERO video game
IEEE Transactions on Evolutionary Computation
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Evolving strategy for a probabilistic game of imperfect information using genetic programming
Genetic Programming and Evolvable Machines
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
PEEC: evolving efficient connections using Pareto optimality
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Coevolutionary temporal difference learning for Othello
CIG'09 Proceedings of the 5th international conference on Computational Intelligence and Games
Pareto evolution and co-evolution in cognitive game AI synthesis
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Evolving small-board Go players using coevolutionary temporal difference learning with archives
International Journal of Applied Mathematics and Computer Science
The arcade learning environment: an evaluation platform for general agents
Journal of Artificial Intelligence Research
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The Layered Pareto Coevolution Archive (LAPCA) was recently proposed as an effective Coevolutionary Memory (CM) which, under certain assumptions, approximates monotonic progress in coevolution. In this paper, a technique is developed that interfaces the LAPCA algorithm with NeuroEvolution of Augmenting Topologies (NEAT), a method to evolve neural networks with demonstrated efficiency in game playing domains. In addition, the behavior of LAPCA is analyzed for the first time in a complex game-playing domain: evolving neural network controllers for the game Pong. The technique is shown to keep the total number of evaluations in the order of those required by NEAT, making it applicable to complex domains. Pong players evolved with a LAPCA and with the Hall of Fame (HOF) perform equally well, but the LAPCA is shown to require significantly less space than the HOF. Therefore, combining NEAT and LAPCA is found to be an effective approach to coevolution.