HiPOP: Hierarchical Partial-Order Planning
نویسندگان
چکیده
This paper describes a new planner, HiPOP (Hierarchical Partial-Order Planner), which is domain-configurable and uses POP techniques to create hierarchical time-flexible plans. HiPOP takes as inputs a description of a domain, a problem, and some optional userdefined search-control knowledge. This additional knowledge takes the form of a set of abstract actions with optional methods to achieve them. HiPOP uses this knowledge to enrich the output by providing a hierarchical time-flexible partial-order plan that follows the given methods. We show in this paper how to use this additional knowledge in a POP algorithm and provide results on a domain with a strong hierarchy of actions. We compare our approach with other temporal planners on this
منابع مشابه
Hybrid Planning Heuristics Based on Task Decomposition Graphs
Hybrid Planning combines Hierarchical Task Network (HTN) planning with concepts known from Partial-Order Causal-Link (POCL) planning. We introduce novel heuristics for Hybrid Planning that estimate the number of necessary modifications to turn a partial plan into a solution. These estimates are based on the task decomposition graph that contains all decompositions of the abstract tasks in the p...
متن کاملComparing Partial Order Planning and Task Reduction Planning: A preliminary report
Although task reduction (HTN) planning historically preceded partial order (PO) planning, and is understood to be more general than the latter, very little analysis has been done regarding its performance. Part of the reason for this has been the lack of systematic understanding of the functionalities provided by HTN planning over and above that of partial order planning. HTN planning has been ...
متن کاملControl Strategies in HTN Planning: Theory Versus Practice
AI planning techniques are beginning to find use in a number of practical planning domains. However, the backward-chaining and partial-order-planning control strategies traditionally used in AI planning systems are not necessarily the best ones to use for practical planning problems. In this paper, we discuss some of the difficulties that can result from the use of backward chaining and partial...
متن کاملHTN-Style Planning in Relational POMDPs Using First-Order FSCs
In this paper, a novel approach to hierarchical planning under partial observability in relational domains is presented. It combines hierarchical task network planning with the finite state controller (FSC) policy representation for partially observable Markov decision processes. Based on a new first-order generalization of FSCs, action hierarchies are defined as in traditional hierarchical pla...
متن کاملPlanning for Machining Workpieces with a Partial-Order, Nonlinear Planner
We describe a hybrid architecture supporting planning for machining workpieces. The architecture is built around CAPLAN, a partial-order nonlinear planner that represents the plan already generated and allows external control decision made by special purpose programs or by the user. To make planning more efficient, the domain is hierarchically modelled. Based on this hierarchical representation...
متن کامل