Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Automatically Reinforcing a Game AI   A recent research trend in Artificial Intelligence (AI) is the combination of
several programs into one single, stronger, program; this is termed portfolio
methods. We here investigate the application of such methods to Game Playing
Programs (GPPs). In addition, we consider the case in which only one GPP is
available - by decomposing this single GPP into several ones through the use of
parameters or even simply random seeds. These portfolio methods are trained in
a learning phase. We propose two different offline approaches. The simplest
one, BestArm, is a straightforward optimization of seeds or parame- ters; it
performs quite well against the original GPP, but performs poorly against an
opponent which repeats games and learns. The second one, namely Nash-portfolio,
performs similarly in a "one game" test, and is much more robust against an
opponent who learns. We also propose an online learning portfolio, which tests
several of the GPP repeatedly and progressively switches to the best one -
using a bandit algorithm.

13
The categories of this paper are: quant-ph
8
The categories of this paper are: hep-ex
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics
34
The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
27
The categories of this paper are: comp-gas
37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an
5
The categories of this paper are: gr-qc
19
The categories of this paper are: eess
29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat