Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learn to Exceed: Stereo Inverse Reinforcement Learning with Concurrent
  Policy Optimization   In this paper, we study the problem of obtaining a control policy that can
mimic and then outperform expert demonstrations in Markov decision processes
where the reward function is unknown to the learning agent. One main relevant
approach is the inverse reinforcement learning (IRL), which mainly focuses on
inferring a reward function from expert demonstrations. The obtained control
policy by IRL and the associated algorithms, however, can hardly outperform
expert demonstrations. To overcome this limitation, we propose a novel method
that enables the learning agent to outperform the demonstrator via a new
concurrent reward and action policy learning approach. In particular, we first
propose a new stereo utility definition that aims to address the bias in the
interpretation of expert demonstrations. We then propose a loss function for
the learning agent to learn reward and action policies concurrently such that
the learning agent can outperform expert demonstrations. The performance of the
proposed method is first demonstrated in OpenAI environments. Further efforts
are conducted to experimentally validate the proposed method via an indoor
drone flight scenario.

13
The categories of this paper are: quant-ph
3
The categories of this paper are: physics
20
The categories of this paper are: acc-phys
15
The categories of this paper are: nucl-ex
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org
7
The categories of this paper are: hep-th
12
The categories of this paper are: nucl-th
9
The categories of this paper are: nlin
25
The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph
24
The categories of this paper are: dg-ga
0
The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
23
The categories of this paper are: solv-int