标题： 深度有界认知规划 显示英文标题

标题： Depth-Bounded Epistemic Planning

摘要： 我们提出了一种基于动态认识逻辑（DEL）的认识规划新算法。 新颖之处在于，我们将规划代理的推理深度限制在一个上限b，这意味着规划代理只能最多推理到（模态）深度b的高阶知识。 然后我们通过迭代增加b的值来计算所需推理深度最低的计划。 该算法的核心依赖于一种新型的“规范”b-二分图收缩，它通过构造保证唯一的最小模型。 这使得状态相对于标准的二分图收缩更小，并能够高效地检查已访问的状态。 我们在推理深度有适当限制的情况下，证明了我们规划算法的正确性和完备性，并且对于一个限制b，它在(b+1)-EXPTIME时间内运行。 我们在一个新的认识规划器DAEDALUS中实现了该算法，并与EFP 2.0规划器在文献中的多个基准上进行了比较，展示了有效的性能提升。 显示英文摘要

摘要： We propose a novel algorithm for epistemic planning based on dynamic epistemic logic (DEL). The novelty is that we limit the depth of reasoning of the planning agent to an upper bound b, meaning that the planning agent can only reason about higher-order knowledge to at most (modal) depth b. We then compute a plan requiring the lowest reasoning depth by iteratively incrementing the value of b. The algorithm relies at its core on a new type of "canonical" b-bisimulation contraction that guarantees unique minimal models by construction. This yields smaller states wrt. standard bisimulation contractions, and enables to efficiently check for visited states. We show soundness and completeness of our planning algorithm, under suitable bounds on reasoning depth, and that, for a bound b, it runs in (b+1)-EXPTIME. We implement the algorithm in a novel epistemic planner, DAEDALUS, and compare it to the EFP 2.0 planner on several benchmarks from the literature, showing effective performance improvements.