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Chapter 6 Planning-Graph Techniques

Chapter 6 Planning-Graph Techniques. g 1. a 1. a 4. g 4. g 2. g 0. a 2. s 0. a 5. g 5. a 3. g 3. Motivation. A big source of inefficiency in search algorithms is the branching factor the number of children of each node e.g., a backward search may try lots of actions

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Graphplan

Graphplan. GRAPHPLAN. Many Planning Systems now use these Ideas: GraphPlan IPP STAN SGP Blackbox Medic Runs orders of magnitude faster than partial order planners (as POP, SNLP, UFPOP, etc.). GraphPlan: THE BASIC IDEA. 1. Construct the (initial) Planning Graph

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510 views • 30 slides

Chapter 6 Planning-Graph Techniques

Lecture slides for Automated Planning: Theory and Practice. Chapter 6 Planning-Graph Techniques. Dana S. Nau CMSC 722, AI Planning University of Maryland, Fall 2004. g 1. a 1. a 4. g 4. g 2. g 0. a 2. s 0. a 5. g 5. a 3. g 3. Motivation.

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335 views • 19 slides

Part III Heuristics and Control Strategies

Part III Heuristics and Control Strategies. Motivation for Part III of the text Book. Domain-independent planners suffer from combinatorial complexity Planning is in the worst case intractable Need ways to control the search Search heuristics (Chapter 9) Pruning rules (Chapter 10)

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194 views • 9 slides

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Chapter 6 Planning-Graph Techniques

Graphplan

Chapter 6 Planning-Graph Techniques

Part III Heuristics and Control Strategies