Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Minimum Relative Entropy Controller for Undiscounted Markov Decision
  Processes   Adaptive control problems are notoriously difficult to solve even in the
presence of plant-specific controllers. One way to by-pass the intractable
computation of the optimal policy is to restate the adaptive control as the
minimization of the relative entropy of a controller that ignores the true
plant dynamics from an informed controller. The solution is given by the
Bayesian control rule-a set of equations characterizing a stochastic adaptive
controller for the class of possible plant dynamics. Here, the Bayesian control
rule is applied to derive BCR-MDP, a controller to solve undiscounted Markov
decision processes with finite state and action spaces and unknown dynamics. In
particular, we derive a non-parametric conjugate prior distribution over the
policy space that encapsulates the agent's whole relevant history and we
present a Gibbs sampler to draw random policies from this distribution.
Preliminary results show that BCR-MDP successfully avoids sub-optimal limit
cycles due to its built-in mechanism to balance exploration versus
exploitation.

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The categories of this paper are: math-ph
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The categories of this paper are: nlin
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The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
0
The categories of this paper are: hep-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: gr-qc
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The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio
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The categories of this paper are: bayes-an
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The categories of this paper are: adap-org
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The categories of this paper are: hep-th
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The categories of this paper are: stat
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The categories of this paper are: q-fin
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The categories of this paper are: quant-ph
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The categories of this paper are: solv-int