Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Interpretable performance analysis towards offline reinforcement
  learning: A dataset perspective   Offline reinforcement learning (RL) has increasingly become the focus of the
artificial intelligent research due to its wide real-world applications where
the collection of data may be difficult, time-consuming, or costly. In this
paper, we first propose a two-fold taxonomy for existing offline RL algorithms
from the perspective of exploration and exploitation tendency. Secondly, we
derive the explicit expression of the upper bound of extrapolation error and
explore the correlation between the performance of different types of
algorithms and the distribution of actions under states. Specifically, we relax
the strict assumption on the sufficiently large amount of state-action tuples.
Accordingly, we provably explain why batch constrained Q-learning (BCQ)
performs better than other existing techniques. Thirdly, after identifying the
weakness of BCQ on dataset of low mean episode returns, we propose a modified
variant based on top return selection mechanism, which is proved to be able to
gain state-of-the-art performance on various datasets. Lastly, we create a
benchmark platform on the Atari domain, entitled RL easy go (RLEG), at an
estimated cost of more than 0.3 million dollars. We make it open-source for
fair and comprehensive competitions between offline RL algorithms with complete
datasets and checkpoints being provided.

24
The categories of this paper are: dg-ga
19
The categories of this paper are: eess
22
The categories of this paper are: chao-dyn
2
The categories of this paper are: math
14
The categories of this paper are: math-ph
36
The categories of this paper are: cmp-lg
32
The categories of this paper are: atom-ph
7
The categories of this paper are: hep-th
37
The categories of this paper are: supr-con
10
The categories of this paper are: q-bio
9
The categories of this paper are: nlin
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th