Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Comparison of Multi-agent and Single-agent Inverse Learning on a
  Simulated Soccer Example   We compare the performance of Inverse Reinforcement Learning (IRL) with the
relative new model of Multi-agent Inverse Reinforcement Learning (MIRL). Before
comparing the methods, we extend a published Bayesian IRL approach that is only
applicable to the case where the reward is only state dependent to a general
one capable of tackling the case where the reward depends on both state and
action. Comparison between IRL and MIRL is made in the context of an abstract
soccer game, using both a game model in which the reward depends only on state
and one in which it depends on both state and action. Results suggest that the
IRL approach performs much worse than the MIRL approach. We speculate that the
underperformance of IRL is because it fails to capture equilibrium information
in the manner possible in MIRL.

12
The categories of this paper are: nucl-th
9
The categories of this paper are: nlin
37
The categories of this paper are: supr-con
20
The categories of this paper are: acc-phys
19
The categories of this paper are: eess
2
The categories of this paper are: math
0
The categories of this paper are: hep-ph
24
The categories of this paper are: dg-ga
25
The categories of this paper are: patt-sol
15
The categories of this paper are: nucl-ex
34
The categories of this paper are: chem-ph
4
The categories of this paper are: cond-mat
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics
16
The categories of this paper are: stat
36
The categories of this paper are: cmp-lg