Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Manipulating the Distributions of Experience used for Self-Play Learning
  in Expert Iteration   Expert Iteration (ExIt) is an effective framework for learning game-playing
policies from self-play. ExIt involves training a policy to mimic the search
behaviour of a tree search algorithm - such as Monte-Carlo tree search - and
using the trained policy to guide it. The policy and the tree search can then
iteratively improve each other, through experience gathered in self-play
between instances of the guided tree search algorithm. This paper outlines
three different approaches for manipulating the distribution of data collected
from self-play, and the procedure that samples batches for learning updates
from the collected data. Firstly, samples in batches are weighted based on the
durations of the episodes in which they were originally experienced. Secondly,
Prioritized Experience Replay is applied within the ExIt framework, to
prioritise sampling experience from which we expect to obtain valuable training
signals. Thirdly, a trained exploratory policy is used to diversify the
trajectories experienced in self-play. This paper summarises the effects of
these manipulations on training performance evaluated in fourteen different
board games. We find major improvements in early training performance in some
games, and minor improvements averaged over fourteen games.

8
The categories of this paper are: hep-ex
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
19
The categories of this paper are: eess
0
The categories of this paper are: hep-ph
23
The categories of this paper are: solv-int
25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
36
The categories of this paper are: cmp-lg
7
The categories of this paper are: hep-th
27
The categories of this paper are: comp-gas
21
The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
3
The categories of this paper are: physics
2
The categories of this paper are: math