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The FF planning system: Fast plan generation through heuristic search

by Jörg Hoffmann, Bernhard Nebel - Journal of Artificial Intelligence Research , 2001
"... We describe and evaluate the algorithmic techniques that are used in the FF planning system. Like the HSP system, FF relies on forward state space search, using a heuristic that estimates goal distances by ignoring delete lists. Unlike HSP's heuristic, our method does not assume facts to be ind ..."
Abstract - Cited by 822 (53 self) - Add to MetaCart
We describe and evaluate the algorithmic techniques that are used in the FF planning system. Like the HSP system, FF relies on forward state space search, using a heuristic that estimates goal distances by ignoring delete lists. Unlike HSP's heuristic, our method does not assume facts

The Fast Downward planning system

by Malte Helmert - 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 ..."
Abstract - Cited by 345 (29 self) - Add to MetaCart
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

Planning as satisfiability

by Henry Kautz, Bart Selman - IN ECAI-92 , 1992
"... We develop a formal model of planning based on satisfiability rather than deduction. The satis ability approach not only provides a more flexible framework for stating di erent kinds of constraints on plans, but also more accurately reflects the theory behind modern constraint-based planning systems ..."
Abstract - Cited by 506 (27 self) - Add to MetaCart
We develop a formal model of planning based on satisfiability rather than deduction. The satis ability approach not only provides a more flexible framework for stating di erent kinds of constraints on plans, but also more accurately reflects the theory behind modern constraint-based planning

SHOP2: An HTN planning system

by Dana Nau, Okhtay Ilghami, Ugur Kuter, J. William Murdock, Dan Wu, Fusun Yaman - Journal of Artificial Intelligence Research , 2003
"... The SHOP2 planning system received one of the awards for distinguished performance in the 2002 International Planning Competition. This paper describes the features of SHOP2 which enabled it to excel in the competition, especially those aspects of SHOP2 that deal with temporal and metric planning do ..."
Abstract - Cited by 273 (30 self) - Add to MetaCart
The SHOP2 planning system received one of the awards for distinguished performance in the 2002 International Planning Competition. This paper describes the features of SHOP2 which enabled it to excel in the competition, especially those aspects of SHOP2 that deal with temporal and metric planning

Planning Algorithms

by Steven M LaValle , 2004
"... This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning ..."
Abstract - Cited by 1108 (51 self) - Add to MetaCart
, planning under uncertainty, sensor-based planning, visibility, decision-theoretic planning, game theory, information spaces, reinforcement learning, nonlinear systems, trajectory planning, nonholonomic planning, and kinodynamic planning.

Pushing the Envelope: Planning, Propositional Logic, and Stochastic Search

by Henry Kautz, Bart Selman , 1996
"... Planning is a notoriously hard combinatorial search problem. In many interesting domains, current planning algorithms fail to scale up gracefully. By combining a general, stochastic search algorithm and appropriate problem encodings based on propositional logic, we are able to solve hard planning pr ..."
Abstract - Cited by 579 (32 self) - Add to MetaCart
problems many times faster than the best current planning systems. Although stochastic methods have been shown to be very e ective on a wide range of scheduling problems, this is the rst demonstration of its power on truly challenging classical planning instances. This work also provides a new perspective

Fast Planning Through Planning Graph Analysis

by Avrim L. Blum, Merrick L. Furst - ARTIFICIAL INTELLIGENCE , 1995
"... We introduce a new approach to planning in STRIPS-like domains based on constructing and analyzing a compact structure we call a Planning Graph. We describe a new planner, Graphplan, that uses this paradigm. Graphplan always returns a shortest possible partial-order plan, or states that no valid pla ..."
Abstract - Cited by 1165 (3 self) - Add to MetaCart
We introduce a new approach to planning in STRIPS-like domains based on constructing and analyzing a compact structure we call a Planning Graph. We describe a new planner, Graphplan, that uses this paradigm. Graphplan always returns a shortest possible partial-order plan, or states that no valid

Randomized kinodynamic planning

by Steven M. Lavalle, James J. Kuffner, Jr. - THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH 2001; 20; 378 , 2001
"... This paper presents the first randomized approach to kinodynamic planning (also known as trajectory planning or trajectory design). The task is to determine control inputs to drive a robot from an initial configuration and velocity to a goal configuration and velocity while obeying physically based ..."
Abstract - Cited by 620 (36 self) - Add to MetaCart
dynamical models and avoiding obstacles in the robot’s environment. The authors consider generic systems that express the nonlinear dynamics of a robot in terms of the robot’s high-dimensional configuration space. Kinodynamic planning is treated as a motion-planning problem in a higher dimensional state

Decision-Theoretic Planning: Structural Assumptions and Computational Leverage

by Craig Boutilier, Thomas Dean, Steve Hanks - JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH , 1999
"... Planning under uncertainty is a central problem in the study of automated sequential decision making, and has been addressed by researchers in many different fields, including AI planning, decision analysis, operations research, control theory and economics. While the assumptions and perspectives ..."
Abstract - Cited by 510 (4 self) - Add to MetaCart
Planning under uncertainty is a central problem in the study of automated sequential decision making, and has been addressed by researchers in many different fields, including AI planning, decision analysis, operations research, control theory and economics. While the assumptions

Plans And Resource-Bounded Practical Reasoning

by Michael E. Bratman, David J. Israel, Martha E. Pollack - COMPUTATIONAL INTELLIGENCE, 4(4):349-355, 1988 , 1988
"... An architecture for a rational agent must allow for means-end reasoning, for the weighing of competing alternatives, and for interactions between these two forms of reasoning. Such an architecture must also address the problem of resource boundedness. We sketch a solution of the first problem that p ..."
Abstract - Cited by 485 (19 self) - Add to MetaCart
that points the way to a solution of the second. In particular, we present a high-level specification of the practical-reasoning component of an architecture for a resource-bounded rational agent. In this architecture, a major role of the agent's plans is to constrain the amount of further practical
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