Guiding a Reinforcement Learner with Natural Language Advice: Initial Results in RoboCup Soccer (2004)
We describe our current efforts towards creating a reinforcement learner that learns both from reinforcements provided by its environment and from human-generated advice. Our research involves two complementary components: (a) mapping advice expressed in English to a formal advice language and (b) using advice expressed in a formal notation in a reinforcement learner. We use a subtask of the challenging RoboCup simulated soccer task as our testbed.
In The AAAI-2004 Workshop on Supervisory Control of Learning and Adaptive Systems, July 2004.

Gregory Kuhlmann Ph.D. Alumni kuhlmann [at] cs utexas edu
Raymond J. Mooney Faculty mooney [at] cs utexas edu
Peter Stone Faculty pstone [at] cs utexas edu