Robot Learning From Demonstration
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Implicit Imitation in Multiagent Reinforcement Learning
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Strongly Typed Genetic Programming in Evolving Cooperation Strategies
Proceedings of the 6th International Conference on Genetic Algorithms
Learning to Communicate Through Imitation in Autonomous Robots
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
Evolutionary On-line Learning of Cooperative Behavior with Situation-Action-Pairs
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Imitation as a mechanism of cultural transmission
Artificial Life
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We present a modification to evolutionary on-line learning of cooperative behavior, based on a special action "learn", that allows the performance of a new agent replacing an old agent with somewhat different abilities in an experienced team to be improved. The general idea is to make us of the strategy of the old agent, obtained either directly or by the model the other team members made of it. This would be used as a seed strategy in the on-line learning process providing a focus to the process. This way, the flexibility of on-line learning remains, and the new agent is much less prone to making "beginner" mistakes that may prevent achievement of the team goal. Experiments with rather different variants of the pursuit game show that our method allows new agents to overcome the difference in abilities rather quickly. Thus, team performance is much better than when the new agent starts learning from scratch.