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410
Tabu Search -- Part I
, 1989
"... This paper presents the fundamental principles underlying tabu search as a strategy for combinatorial optimization problems. Tabu search has achieved impressive practical successes in applications ranging from scheduling and computer channel balancing to cluster analysis and space planning, and more ..."
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Cited by 680 (11 self)
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This paper presents the fundamental principles underlying tabu search as a strategy for combinatorial optimization problems. Tabu search has achieved impressive practical successes in applications ranging from scheduling and computer channel balancing to cluster analysis and space planning
SEARCH COMPLEXITIES FOR HTN PLANNING
"... Hierarchical Task Network (HTN) planning is the problem of decomposing an initial task into a sequence of executable steps. Often viewed as just a way to encode human knowledge to solve classical planning problems faster, HTN planning is more expressive than classical planning, even to the point of ..."
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of being undecidable in the general case. However, HTN planning is not just a way to solve planning problems faster, but is itself a search problem that can benefit from its own distinct search algorithms and heuristics. The dissertation examines the complexities of various HTN planning problem classes
The Fast Downward planning system
- Journal of Artifical Intelligence Research
, 2006
"... Fast Downward is a classical planning system based on heuristic search. It can deal with general deterministic planning problems encoded in the propositional fragment of PDDL2.2, including advanced features like ADL conditions and effects and derived predicates (axioms). Like other well-known planne ..."
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Cited by 347 (29 self)
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Fast Downward is a classical planning system based on heuristic search. It can deal with general deterministic planning problems encoded in the propositional fragment of PDDL2.2, including advanced features like ADL conditions and effects and derived predicates (axioms). Like other well
On 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 pos-itive effects and preconditions) led to the highly success-ful Relaxed Graphplan heuristic. We present a hierarchy of new computational complexity results for different classes of p ..."
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Cited by 2 (2 self)
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-free HTN planning with task insertion) is polynomial-time computable. Thus, there may be a possibil-ity of using this or other relaxations to develop search heuris-tics for HTN planning. 1
HTN Planning with . . .
"... In this paper, we address the problem of generating preferred plans by combining the procedural control knowledge specified by Hierarchical Task Networks (HTNs) with rich user preferences. To this end, we extend the popular Plan Domain Description Language, PDDL3, to support specification of prefere ..."
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of preferences over HTN constructs. To compute preferred HTN plans, we propose a branch-and-bound algorithm, together with a set of heuristics that, leveraging HTN structure, measure progress towards satisfaction of preferences. Our preference-based planner, HTNPLAN-P, is implemented as an extension of SHOP2. We
Planning with Incomplete Information as Heuristic Search in Belief Space
, 2000
"... The formulation of planning as heuristic search with heuristics derived from problem representations has turned out to be a fruitful approach for classical planning. In this paper, we pursue a similar idea in the context planning with incomplete information. Planning with incomplete information ..."
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Cited by 225 (34 self)
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The formulation of planning as heuristic search with heuristics derived from problem representations has turned out to be a fruitful approach for classical planning. In this paper, we pursue a similar idea in the context planning with incomplete information. Planning with incomplete
Admissible Heuristics for Optimal Planning
- IN PROCEEDINGS OF AIPS-00
, 2000
"... hsp and hspr are two recent planners that search the state-space using an heuristic function extracted from Strips encodings. hsp does a forward search from the initial state recomputing the heuristic in every state, while hspr does a regression search from the goal computing a suitable representati ..."
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Cited by 196 (24 self)
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is not admissible and the search algorithms are not optimal. In this paper we address this problem. We formulate a new admissible heuristic for planning, use it to guide an ida search, and empirically evaluate the resulting optimal planner over a number of domains. The main contribution is the idea underlying
Combining Domain-Independent Planning and HTN Planning: The Duet Planner
, 2008
"... Despite the recent advances in planning for classical domains, the question of how to use domain knowledge in planning is yet to be completely and clearly answered. Some of the existing planners use domain-independent search heuristics, and some others depend on intensively-engineered domainspecific ..."
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Cited by 15 (6 self)
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Despite the recent advances in planning for classical domains, the question of how to use domain knowledge in planning is yet to be completely and clearly answered. Some of the existing planners use domain-independent search heuristics, and some others depend on intensively
On planning with preferences in HTN
- In Proc. of the 12th Int’l Workshop on Non-Monotonic Reasoning (NMR
, 2008
"... In this paper, we address the problem of generating preferred plans by combining the procedural control knowledge specified by Hierarchical Task Networks (HTNs) with rich qualitative user preferences. The outcome of our work is a language for specifying user preferences, tailored to HTN planning, to ..."
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Cited by 7 (5 self)
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, together with a provably optimal preference-based planner, HTNPREF, that is implemented as an extension of SHOP2. To compute preferred plans, we propose an approach based on forward-chaining heuristic search. Our heuristic uses an admissible evaluation function measuring the satisfaction of preferences
Heuristically Guided Constraint Satisfaction for Planning
"... Constraint satisfaction techniques have been used in Artificial Intelligence planning for many years. As with the original planning problem formulation, the CSP model’s complexity can lead to a very large search space for all but the simplest of problems. Without additional guidance, the CSP solver ..."
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will rely on standard CSP heuristics and search methods. Better use can be made of the CSP framework if the search is informed by the structure of the planning problem. This paper discusses a goal-centric, variable / value selection heuristic method of guiding the search for a solution to a constraint
Results 1 - 10
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410