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AI PLANNING BASED QUASI-MONTECARLO SIMULATION METHOD FOR PROBABILISTIC PLANNING

  • US 20110238614A1
  • Filed: 03/29/2010
  • Published: 09/29/2011
  • Est. Priority Date: 03/29/2010
  • Status: Active Grant
First Claim
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1. A computer-implemented method for AI planning based quasi-Monte Carlo simulation for probabilistic planning, comprising:

  • using a computer processor, receiving an initial state and a description of a target domain into computer memory;

    generating a set of possible actions for the initial state;

    for each action in the set of the possible actions, performing a sequence of actions, comprising;

    generating a set of sample future outcomes;

    generating solutions for each of the sample future outcomes;

    using an AI planner, generating a set of future outcome solutions that are low probability and high-impact;

    aggregating the solutions generated by the AI planner with the sample future outcomes; and

    analyzing the aggregated set of future outcome solutions;

    selecting a best action based at least partially on the analysis of the aggregated set of future outcome solutions; and

    outputting the selected best action to computer memory.

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