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Environment-Independent Task Specifications via GLTL

14 Apr 2017 • Michael L. Littman • Ufuk Topcu • Jie Fu • Charles Isbell • Min Wen • James Macglashan

We propose a new task-specification language for Markov decision processes that is designed to be an improvement over reward functions by being environment independent. The language is a variant of Linear Temporal Logic (LTL) that is extended to probabilistic specifications in a way that permits approximations to be learned in finite time... (read more)

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