The design and analysis of a computational model of cooperative coevolution
The design and analysis of a computational model of cooperative coevolution
The dynamics of reinforcement learning in cooperative multiagent systems
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Proceedings of the 6th International Conference on Genetic Algorithms
An Algorithm for Distributed Reinforcement Learning in Cooperative Multi-Agent Systems
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Co-evolving Soccer Softbot Team Coordination with Genetic Programming
RoboCup-97: Robot Soccer World Cup I
Analyzing cooperative coevolution with evolutionary game theory
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
Cooperative Multi-Agent Learning: The State of the Art
Autonomous Agents and Multi-Agent Systems
Archive-based cooperative coevolutionary algorithms
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Selecting informative actions improves cooperative multiagent learning
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Generative encoding for multiagent learning
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective
The Journal of Machine Learning Research
A First Study on the Use of Coevolutionary Algorithms for Instance and Feature Selection
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Coevolution of heterogeneous multi-robot teams
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Evolving policy geometry for scalable multiagent learning
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Theoretical convergence guarantees for cooperative coevolutionary algorithms
Evolutionary Computation
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
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Evolutionary computation is a useful technique for learning behaviors in multiagent systems. Among the several types of evolutionary computation, one natural and popular method is to coevolve multi-agent behaviors in multiple, cooperating populations. Recent research has suggested that revolutionary systems may favor stability rather than performance in some domains. In order to improve upon existing methods, this paper examines the idea of modifying traditional coevolution, biasing it to search for maximal rewards. We introduce a theoretical justification of the improved method and present experiments in three problem domains. We conclude that biasing can help coevolution find better results in some multiagent problem domains.