Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Global Optimization for Value Function Approximation   Existing value function approximation methods have been successfully used in
many applications, but they often lack useful a priori error bounds. We propose
a new approximate bilinear programming formulation of value function
approximation, which employs global optimization. The formulation provides
strong a priori guarantees on both robust and expected policy loss by
minimizing specific norms of the Bellman residual. Solving a bilinear program
optimally is NP-hard, but this is unavoidable because the Bellman-residual
minimization itself is NP-hard. We describe and analyze both optimal and
approximate algorithms for solving bilinear programs. The analysis shows that
this algorithm offers a convergent generalization of approximate policy
iteration. We also briefly analyze the behavior of bilinear programming
algorithms under incomplete samples. Finally, we demonstrate that the proposed
approach can consistently minimize the Bellman residual on simple benchmark
problems.

21
The categories of this paper are: adap-org
28
The categories of this paper are: alg-geom
34
The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
35
The categories of this paper are: mtrl-th
8
The categories of this paper are: hep-ex
3
The categories of this paper are: physics
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
10
The categories of this paper are: q-bio
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
27
The categories of this paper are: comp-gas