Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Integrating Planning and Execution in Stochastic Domains   We investigate planning in time-critical domains represented as Markov
Decision Processes, showing that search based techniques can be a very powerful
method for finding close to optimal plans. To reduce the computational cost of
planning in these domains, we execute actions as we construct the plan, and
sacrifice optimality by searching to a fixed depth and using a heuristic
function to estimate the value of states. Although this paper concentrates on
the search algorithm, we also discuss ways of constructing heuristic functions
suitable for this approach. Our results show that by interleaving search and
execution, close to optimal policies can be found without the computational
requirements of other approaches.

19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga
27
The categories of this paper are: comp-gas
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph
22
The categories of this paper are: chao-dyn
13
The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
35
The categories of this paper are: mtrl-th
12
The categories of this paper are: nucl-th
5
The categories of this paper are: gr-qc
23
The categories of this paper are: solv-int
21
The categories of this paper are: adap-org