TEACHING MULTIPLE INVERSE REINFORCEMENT LEARNERS

Teaching Multiple Inverse Reinforcement Learners

In this paper, we propose the first machine teaching algorithm for Quarter Zips multiple inverse reinforcement learners.As our initial contribution, we formalize the problem of optimally teaching a sequential task to a heterogeneous class of learners.We then contribute a theoretical analysis of such problem, identifying conditions under which it is

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