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AI planning based quasi-montecarlo simulation method for probabilistic planning

机译:基于人工智能计划的概率规划准蒙特卡洛仿真方法

摘要

A computer-based method and system for AI planning based quasi-Monte Carlo simulation for probabilistic planning are provided. The method includes generating a set of possible actions for an initial state, 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, combining the solutions generated from each of the sample future outcomes with the future outcome solutions generated by the AI Planner into an aggregated set of future outcome solutions, 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.
机译:提供了一种基于计算机的方法和系统,用于基于AI计划的概率计划的准蒙特卡洛模拟。该方法包括为初始状态生成一组可能的动作,生成一组样本未来结果,使用AI计划程序为每个样本未来结果生成解决方案,生成一组低概率和高概率的未来结果解决方案-影响,将每个样本未来结果生成的解决方案与AI计划程序生成的未来结果解决方案组合到一组未来结果解决方案的汇总中,分析该组未来结果解决方案的汇总,并至少部分地选择最佳行动分析未来结果解决方案的汇总集合,并将所选的最佳操作输出到计算机内存。

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