Guiding a Reinforcement Learner with Natural Language Advice: Initial Results in RoboCup Soccer
Gregory Kuhlmann and Peter Stone and Raymond J. Mooney and Jude W. Shavlik · National Conference on Artificial Intelligence · 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 (Noda et al. 1998) as our testbed.