Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Interaction-limited Inverse Reinforcement Learning   This paper proposes an inverse reinforcement learning (IRL) framework to
accelerate learning when the learner-teacher \textit{interaction} is
\textit{limited} during training. Our setting is motivated by the realistic
scenarios where a helpful teacher is not available or when the teacher cannot
access the learning dynamics of the student. We present two different training
strategies: Curriculum Inverse Reinforcement Learning (CIRL) covering the
teacher's perspective, and Self-Paced Inverse Reinforcement Learning (SPIRL)
focusing on the learner's perspective. Using experiments in simulations and
experiments with a real robot learning a task from a human demonstrator, we
show that our training strategies can allow a faster training than a random
teacher for CIRL and than a batch learner for SPIRL.

17
The categories of this paper are: q-fin
35
The categories of this paper are: mtrl-th
21
The categories of this paper are: adap-org
31
The categories of this paper are: ao-sci
14
The categories of this paper are: math-ph
5
The categories of this paper are: gr-qc
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
29
The categories of this paper are: funct-an
22
The categories of this paper are: chao-dyn
11
The categories of this paper are: hep-lat
37
The categories of this paper are: supr-con
30
The categories of this paper are: q-alg
8
The categories of this paper are: hep-ex
19
The categories of this paper are: eess
13
The categories of this paper are: quant-ph