强循环策略的符号规划

V. B. D. Santos, L. N. Barros, Maria Viviane de Menezes
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引用次数: 0

摘要

完全可观察非确定性FOND规划的解决方案分为弱、强或强循环,表明由于行动的不确定性而达到目标状态的不同方法。本文提出了一种新的算法来解决强循环策略中agent总能达到目标的FOND规划问题,该算法在公平性假设下执行最终会退出所有现有循环。称为pactl - sm - strongcyclic的计划器基于使用alpha-CTL逻辑的符号模型检查:CTL的扩展,考虑转换背后的操作。据我们所知,这是第一个对动作(而不是状态转换关系)应用符号推理的强循环策略的FOND规划器,因此可以优于最先进的FOND规划器。
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Symbolic Planning for Strong-Cyclic Policies
A solution for Fully Observable Non-Deterministic FOND planning is classified as weak, strong or strong-cyclic, indicating different ways to reach a goal state due to the non-determinism of the actions. In this paper, we propose a new algorithm to solve FOND planning problems for strong-cyclic policies, where the agent always achieves the goal, under the fairness assumption that execution will eventually exit from all existing cycles. The planner, called Pactl-Sym-StrongCyclic, is based on symbolic model checking using alpha-CTL logic: an extension of CTL that considers actions behind the transitions. To the best of our knowledge, this is the first FOND planner for strong-cyclic policies that applies symbolic reasoning over the actions (and not over the state transition relation), and therefore can outperform state-of-the-art FOND planners.
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