Heuristics for HTN Planning as Satisfiability
نویسنده
چکیده
Classical planning is the problem of synthesizing a sequence of actions to reach the goal state starting from the initial state. Hierarchical task networks (HTNs) have been used as a guidance for solving planning problems where tasks are decomposed into subtasks. Recently, both action-based planning as well as HTNbased planning have been east as SAT. The performance of planning as SAT has been hitherto remarkably improved by using a variety of techniques ̄ However none of these techniques is sensitive to the structure of domain specific knowledge. To bridge this gap, we develop and evaluate several heuristics that are sensitive to the structure of the given domain knowledge (in the form of HTNs), to generate propositional encodings of HTN planning. The resulting encodings are smaller and easier to solve on most of the problems. Given that the current SAT solvers can handle a limited number of variables (10,000) and clauses (100,000) in real time, such heuristics sensitive to the structure of the domain knowledge are important.
منابع مشابه
Hybrid Planning - Theoretical Foundations and Practical Applications
The thesis presents a novel set-theoretic formalization of (propositional) hybrid planning – a planning framework that fuses Hierarchical Task Network (HTN) planning with Partial-Order Causal-Link (POCL) planning. Several sub classes thereof are identified that capture well-known problems such as HTN planning and POCL planning. For these problem classes, the complexity of the plan-existence pro...
متن کاملOn the Feasibility of Planning Graph Style Heuristics for HTN Planning
In classical planning, the polynomial-time computability of propositional delete-free planning (planning with only positive effects and preconditions) led to the highly successful Relaxed Graphplan heuristic. We present a hierarchy of new computational complexity results for different classes of propositional delete-free HTN planning, with two main results: We prove that finding a plan for the ...
متن کاملLearning HTN Method Preconditions and Action Models from Partial Observations
To apply hierarchical task network (HTN) planning to real-world planning problems, one needs to encode the HTN schemata and action models beforehand. However, acquiring such domain knowledge is difficult and time-consuming because the HTN domain definition involves a significant knowledge-engineering effort. A system that can learn the HTN planning domain knowledge automatically would save time...
متن کاملBound to Plan: Exploiting Classical Heuristics via Automatic Translations of Tail-Recursive HTN Problems
Hierarchical Task Network (HTN) planning is a formalism that can express constraints which cannot easily be expressed by classical (non-hierarchical) planning approaches. It enables reasoning about procedural structures and domainspecific search control knowledge. Yet the cornucopia of modern heuristic search techniques remains largely unincorporated in current HTN planners, in part because it ...
متن کاملHybrid 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 کامل