Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Convergence of Value Aggregation for Imitation Learning   Value aggregation is a general framework for solving imitation learning
problems. Based on the idea of data aggregation, it generates a policy sequence
by iteratively interleaving policy optimization and evaluation in an online
learning setting. While the existence of a good policy in the policy sequence
can be guaranteed non-asymptotically, little is known about the convergence of
the sequence or the performance of the last policy. In this paper, we debunk
the common belief that value aggregation always produces a convergent policy
sequence with improving performance. Moreover, we identify a critical stability
condition for convergence and provide a tight non-asymptotic bound on the
performance of the last policy. These new theoretical insights let us stabilize
problems with regularization, which removes the inconvenient process of
identifying the best policy in the policy sequence in stochastic problems.

19
The categories of this paper are: eess
28
The categories of this paper are: alg-geom
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
27
The categories of this paper are: comp-gas
18
The categories of this paper are: econ
14
The categories of this paper are: math-ph
8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
12
The categories of this paper are: nucl-th
26
The categories of this paper are: bayes-an
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat
15
The categories of this paper are: nucl-ex
37
The categories of this paper are: supr-con