Have I Been Here Before? State Memoization in Temporal Planning
Have I Been Here Before? State Memoization in Temporal Planning
复制标题
我以前来过这里吗？
DOI：
--
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
A. Coles
中科院分区：
文献类型：
--
作者：
A. Coles;A. Coles
状态记忆对于启发式前向搜索规划器的良好性能至关重要，它代表了当前最先进的规划方法的很大一部分。在非时间规划中，丢弃之前生成的任何状态就足够了，无论达到该状态所采取的路径如何，唯一的侧面约束是计划成本。我们在本文开始时证明，在时间规划中使用这种技术可能会导致涉及完工时间的指标失去最优性，并且在更具表现力的域的情况下可能会导致完整性的损失。我们确定发生这种情况的具体条件：当前正在执行操作的状态。接下来，我们引入了用于表达时间规划问题的新记忆技术，该技术既保持完整性又保持最优性，解决了确定时间规划中的两个状态何时可以被视为等效的挑战性问题。最后，我们证明这些对于提高 POPF 规划框架中各种时间规划基准的规划性能具有重大影响。
State memoization is critical to the good performance of heuristic forward search planners, which represent a significant proportion of the current state-of-the-art planning approaches. In non-temporal planning it is sufficient to discard any state that has been generated before, regardless of the path taken to reach that state, with the only side-constraint being plan cost. We begin this paper by demonstrating that the use of this technique in temporal planning can lead to loss of optimality with respect to metrics involving makespan and that in the case of more expressive domains can lead to loss of completeness. We identify the specific conditions under which this occurs: states where actions are currently executing. Following from this we introduce new memoization techniques for expressive temporal planning problems that are both completeness and optimality preserving, solving the challenging problem of determining when two states in temporal planning can be considered equivalent. Finally, we demonstrate that these have significant impact on improving the planning performance across a wide range of temporal planning benchmarks in the POPF planning framework.
将推理在时间规划中的使用扩展为前向搜索
DOI：
--
发表时间：
2009
期刊：
--
影响因子：
--
作者：
Coles, A.J
通讯作者：
Coles, A.J