Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fitted Q-Learning for Relational Domains   We consider the problem of Approximate Dynamic Programming in relational
domains. Inspired by the success of fitted Q-learning methods in propositional
settings, we develop the first relational fitted Q-learning algorithms by
representing the value function and Bellman residuals. When we fit the
Q-functions, we show how the two steps of Bellman operator; application and
projection steps can be performed using a gradient-boosting technique. Our
proposed framework performs reasonably well on standard domains without using
domain models and using fewer training trajectories.

24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
13
The categories of this paper are: quant-ph
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
19
The categories of this paper are: eess
12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
17
The categories of this paper are: q-fin
14
The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph
18
The categories of this paper are: econ
31
The categories of this paper are: ao-sci