Experiments in Sequenced Reinforcement Learning of Reactive Tasks by a Mobile Robot

This paper presents an experimental investigation about Reinforcement Learning of multiple reactive behaviors in an autonomous mobile robot. Reactive behaviors are learned concurrently or sequentially in real-time and coping with finite lifespan, limited accuracy, and finite computational resources constraints. Results provide insight into the problems and tradeoffs faced in learning composite behaviors.