An introduction to genetic algorithms
An introduction to genetic algorithms
Coevolutionary search among adversaries
Coevolutionary search among adversaries
ALIFE Proceedings of the sixth international conference on Artificial life
Co-Evolution in the Successful Learning of Backgammon Strategy
Machine Learning
Tracking the Red Queen: Measurements of Adaptive Progress in Co-Evolutionary Simulations
Proceedings of the Third European Conference on Advances in Artificial Life
Competitive Environments Evolve Better Solutions for Complex Tasks
Proceedings of the 5th International Conference on Genetic Algorithms
The Artificial Evolution of Cooperation
AE '95 Selected Papers from the European conference on Artificial Evolution
A Statistical Mechanical Formulation of the Dynamics of Genetic Algorithms
Selected Papers from AISB Workshop on Evolutionary Computing
Evolving 3d morphology and behavior by competition
Artificial Life
The Effects of Representational Bias on Collaboration Methods in Cooperative Coevolution
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Pareto Optimality in Coevolutionary Learning
ECAL '01 Proceedings of the 6th European Conference on Advances in Artificial Life
Competitive genetic algorithms with application to reliability optimal design
Advances in Engineering Software - Civil-comp 2001
Coevolutionary Method for Gene Selection and Parameter Optimization in Microarray Data Analysis
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
Evolving policy geometry for scalable multiagent learning
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Approximating n-player behavioural strategy nash equilibria using coevolution
Proceedings of the 13th annual conference on Genetic and evolutionary computation
The effect of group size and frequency-of-encounter on the evolution of cooperation
ECAL'09 Proceedings of the 10th European conference on Advances in artificial life: Darwin meets von Neumann - Volume Part II
An overview of cooperative and competitive multiagent learning
LAMAS'05 Proceedings of the First international conference on Learning and Adaption in Multi-Agent Systems
Multirobot behavior synchronization through direct neural network communication
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part II
Genetic programming enabled evolution of control policies for dynamic stochastic optimal power flow
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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The fundamental distinction between ordinary evolutionary algorithms (EA) and co-evolutionary algorithms lies in the interaction between coevolving entities. We behave that this property is essentially game-theoretic in nature. Using game theory, we describe extensions that allow familiar mixing-matrix and Markov-chain models of EAs to address coevolutionary algorithm dynamics. We then employ concepts from evolutionary game theory to examine design aspects of conventional coevolutionary algorithms that are poorly understood.