Incremental multi-step Q-learning
Machine Learning - Special issue on reinforcement learning
Practical Reinforcement Learning in Continuous Spaces
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
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Autonomous learning robots have the advantage over manually programmed robots in that they are able to adapt to varying conditions, both internal to the robot (e.g., energy levels) as well as external environmental conditions (e.g. obstacles, light). In this project, there were analized the possibilities to implement a robot that learns how avoid obstacle using online self-adaptation. Initially it was sudied and implemented a robot that explores an unknown path, using touch sensors and an obstacol detector to find its way during the exploration. Finally it was implemented a genetic algorithm on the robot and experimented with using genetic algorithm as a form of robot learning. The robot was built using the Lego RCX.