Interactive Learning from Policy-Dependent Human Feedback

ICML 2017 James MacGlashanMark K HoRobert LoftinBei PengDavid RobertsMatthew E. TaylorMichael L. Littman

For agents and robots to become more useful, they must be able to quickly learn from non-technical users. This paper investigates the problem of interactively learning behaviors communicated by a human teacher using positive and negative feedback... (read more)

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