Refinement Planning: Status and Prospectus

Overview

Planning & Classical Planning

Modeling Classical Planning

The many brands of classical planners

Overview

Refinement Planning: Overview

Partial Plans: Syntax

Partial Plans: Syntax

Partial Plans: Semantics

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Refinement Strategies

Refinement Planning Template

Combining Refinement with Search

Overview

Forward State-space Refinement

Goal-directed State-space Refinements

Position, Relevance and Commitment

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PSR with non-primitive actions

Tractability Refinements

Interleaving Refinements

Overview

Asymptotic Tradeoffs

Empirical Evaluation of Tradeoffs

Subgoal Interactions and Planner Selection

Overview

Improving Performance through Customization

Reducing Search through Disjunctive Representations

Disjunctive Representations

Controlling Refinement through constraint propagation

Planning with Disjunctive Representations

Conclusion

Research Issues

Acknowledgments

Refinement Planning: Status and Prospectus

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Tractability Refinements

Tractability Refinements (contd.)

References: Unifying Classical Planning Approaches (with Srivastava, 1996) ASU CSE TR 96-006 Planning as refinement search: A unified framework for evaluating design tradeoffs in partial order planning (with Knoblock and Yang, 1995) Artificial Intelligence, 1995. Comparing partial order planning and task reduction planning SIGART Bulletin, 1995.

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Progression and Regression

Forward State-space Refinement (FSR)

Goal Directed State-Space Refinements

Backward State-space Refinement (BSR)

Plan-space refinement

Controlled Splitting

Refinement Strategies

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Advantages of the Unified View

Existing plan-space planners