谢琳. 局部满意的启发式搜索算法[J]. 微电子学与计算机, 2011, 28(10): 194-200.
引用本文: 谢琳. 局部满意的启发式搜索算法[J]. 微电子学与计算机, 2011, 28(10): 194-200.
XIE Lin. Heuristic Search for Partial Satisfaction Algorithm[J]. Microelectronics & Computer, 2011, 28(10): 194-200.
Citation: XIE Lin. Heuristic Search for Partial Satisfaction Algorithm[J]. Microelectronics & Computer, 2011, 28(10): 194-200.

局部满意的启发式搜索算法

Heuristic Search for Partial Satisfaction Algorithm

  • 摘要: 在经典规划中, 目标是找到一系列连续的行为, 改变初始状态Z到一些满意的目标状态G.局部满意规划 (PSP) 问题是规划问题中的核心问题之一.在PSP中, 文献1-2给出的每个目标有一个功能值ug≥0, 代表每个目标对于用户的价值;每个行为a∈A, 有一个关联执行代价Ca≥0, 代表它执行每个行为的代价.P为所有有效规划集, p∈G为目标集, 目标是寻找一个规划p在功能ug和执行代价之间寻找最大差, 即arg p∈P max sum (ug) from g∈Gp-sum (Ca) from c∈p 针对局部满意问题, 提出了一种新的启发式搜索算法.该算法经过验证, 取得了明显的效果.

     

    Abstract: In classical planning, the aim is to find a sequence of actions that transforms a given initial state Z to some state satisfying goals G.Partial satisfaction planning is one of key point in planning problem.In partial satisfaction planning1-2, each goal has a utility value ug≥0, representing how mach each goal is worth to a user;each action a∈A has an associated execution cost Ca≥0, representing how costly it is to execute each action.Let P be the set of all valid plans and let Gp∈G be the set of goals achieved by a plan.The objective is to find a plan P that maximizes the difference between total achieved utility u and total cost of all actions: arg p∈P max sum (ug) from g∈Gp-sum (Ca) from c∈p.This article gives a new heuristic search algorithm for partial satisfaction planning.It confirms their effective through the examples.

     

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