Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Policy Synthesis for Factored MDPs with Graph Temporal Logic
  Specifications   We study the synthesis of policies for multi-agent systems to implement
spatial-temporal tasks. We formalize the problem as a factored Markov decision
process subject to so-called graph temporal logic specifications. The
transition function and the spatial-temporal task of each agent depend on the
agent itself and its neighboring agents. The structure in the model and the
specifications enable to develop a distributed algorithm that, given a factored
Markov decision process and a graph temporal logic formula, decomposes the
synthesis problem into a set of smaller synthesis problems, one for each agent.
We prove that the algorithm runs in time linear in the total number of agents.
The size of the synthesis problem for each agent is exponential only in the
number of neighboring agents, which is typically much smaller than the number
of agents. We demonstrate the algorithm in case studies on disease control and
urban security. The numerical examples show that the algorithm can scale to
hundreds of agents.

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The categories of this paper are: nucl-th
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The categories of this paper are: q-fin
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The categories of this paper are: eess
31
The categories of this paper are: ao-sci
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
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The categories of this paper are: gr-qc
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The categories of this paper are: acc-phys
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The categories of this paper are: funct-an
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The categories of this paper are: bayes-an
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The categories of this paper are: q-alg
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The categories of this paper are: stat
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The categories of this paper are: quant-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: physics
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The categories of this paper are: hep-ex