Predictive Learning from Demonstration [chapter]

Erik A. Billing, Thomas Hellström, Lars-Erik Janlert
2011 Communications in Computer and Information Science  
A model-free learning algorithm called Predictive Sequence Learning (PSL) is presented and evaluated in a robot Learning from Demonstration (LFD) setting. PSL is inspired by several functional models of the brain. It constructs sequences of predictable sensory-motor patterns, without relying on predened higher-level concepts. The algorithm is demonstrated on a Khepera II robot in four dierent tasks. During training, PSL generates a hypothesis library from demonstrated data. The library is then
more » ... sed to control the robot by continually predicting the next action, based on the sequence of passed sensor and motor events. In this way, the robot reproduces the demonstrated behavior. PSL is able to successfully learn and repeat three elementary tasks, but is unable to repeat a fourth, composed behavior. The results indicate that PSL is suitable for learning problems up to a certain complexity, while higher level coordination is required for learning more complex behaviors.
doi:10.1007/978-3-642-19890-8_14 fatcat:j5npriqfsbfk5jvuwff3vvdwfy