Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Theoretically-Grounded Policy Advice from Multiple Teachers in
  Reinforcement Learning Settings with Applications to Negative Transfer   Policy advice is a transfer learning method where a student agent is able to
learn faster via advice from a teacher. However, both this and other
reinforcement learning transfer methods have little theoretical analysis. This
paper formally defines a setting where multiple teacher agents can provide
advice to a student and introduces an algorithm to leverage both autonomous
exploration and teacher's advice. Our regret bounds justify the intuition that
good teachers help while bad teachers hurt. Using our formalization, we are
also able to quantify, for the first time, when negative transfer can occur
within such a reinforcement learning setting.

10
The categories of this paper are: q-bio
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
15
The categories of this paper are: nucl-ex
7
The categories of this paper are: hep-th
11
The categories of this paper are: hep-lat
25
The categories of this paper are: patt-sol
9
The categories of this paper are: nlin
26
The categories of this paper are: bayes-an
16
The categories of this paper are: stat
14
The categories of this paper are: math-ph
2
The categories of this paper are: math
21
The categories of this paper are: adap-org
36
The categories of this paper are: cmp-lg
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th