Interactive Learning of State Representation through Natural Language Instruction and Explanation

7 Oct 2017 Qiaozi Gao Lanbo She Joyce Y. Chai

One significant simplification in most previous work on robot learning is the closed-world assumption where the robot is assumed to know ahead of time a complete set of predicates describing the state of the physical world. However, robots are not likely to have a complete model of the world especially when learning a new task... (read more)

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