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Available4.4
25 reviews
ISBN 10: 1558608567
ISBN 13: 9781558608566
Author: Malik Ghallab, Dana Nau, Paolo Traverso
Automated planning technology now plays a significant role in a variety of demanding applications, ranging from controlling space vehicles and robots to playing the game of bridge. These real-world applications create new opportunities for synergy between theory and practice: observing what works well in practice leads to better theories of planning, and better theories lead to better performance of practical applications.
Automated Planning mirrors this dialogue by offering a comprehensive, up-to-date resource on both the theory and practice of automated planning. The book goes well beyond classical planning, to include temporal planning, resource scheduling, planning under uncertainty, and modern techniques for plan generation, such as task decomposition, propositional satisfiability, constraint satisfaction, and model checking.
The authors combine over 30 years experience in planning research and development to offer an invaluable text to researchers, professionals, and graduate students.
Chapter 1. Introduction and Overview
1.1 First Intuitions on Planning
1.2 Forms of Planning
1.3 Domain-Independent Planning
1.4 Conceptual Model for Planning
1.5 Restricted Model
1.6 Extended Models
1.7 A Running Example: Dock-Worker Robots
Part I: Classical Planning
Chapter 2. Representations for Classical Planning
2.1 Introduction
2.2 Set-Theoretic Representation
2.3 Classical Representation
2.4 Extending the Classical Representation
2.5 State-Variable Representation
2.6 Comparisons
2.7 Discussion and Historical Remarks
2.8 Exercises
Chapter 3. Complexity of Classical Planning
3.1 Introduction
3.2 Preliminaries
3.3 Decidability and Undecidability Results
3.4 Complexity Results
3.5 Limitations
3.6 Discussion and Historical Remarks
3.7 Exercises
Chapter 4. State-Space Planning
4.1 Introduction
4.2 Forward Search
4.3 Backward Search
4.4 The STRIPS Algorithm
4.5 Domain-Specific State-Space Planning
4.6 Discussion and Historical Remarks
4.7 Exercises
Chapter 5. Plan-Space Planning
5.1 Introduction
5.2 The Search Space of Partial Plans
5.3 Solution Plans
5.4 Algorithms for Plan-Space Planning
5.5 Extensions
5.6 Plan-Space versus State-Space Planning
5.7 Discussion and Historical Remarks
5.8 Exercises
Part II: Neoclassical Planning
Chapter 6. Planning-Graph Techniques
6.1 Introduction
6.2 Planning Graphs
6.3 The Graphplan Planner
6.4 Extensions and Improvements of Graphplan
6.5 Discussion and Historical Remarks
6.6 Exercises
Chapter 7. Propositional Satisfiability Techniques
7.1 Introduction
7.2 Planning Problems as Satisfiability Problems
7.3 Planning by Satisfiability
7.4 Different Encodings
7.5 Discussion and Historical Remarks
7.6 Exercises
Chapter 8. Constraint Satisfaction Techniques
8.1 Introduction
8.2 Constraint Satisfaction Problems
8.3 Planning Problems as CSPs
8.4 CSP Techniques and Algorithms
8.5 Extended CSP Models
8.6 CSP Techniques in Planning
8.7 Discussion and Historical Remarks
8.8 Exercises
Part III: Heuristics and Control Strategies
Chapter 9. Heuristics in Planning
9.1 Introduction
9.2 Design Principle for Heuristics: Relaxation
9.3 Heuristics for State-Space Planning
9.4 Heuristics for Plan-Space Planning
9.5 Discussion and Historical Remarks
9.6 Exercises
Chapter 10. Control Rules in Planning
10.1 Introduction
10.2 Simple Temporal Logic
10.3 Progression
10.4 Planning Procedure
10.5 Extensions
10.6 Extended Goals
10.7 Discussion and Historical Remarks
10.8 Exercises
Chapter 11. Hierarchical Task Network Planning
11.1 Introduction
11.2 STN Planning
11.3 Total-Order STN Planning
11.4 Partial-Order STN Planning
11.5 HTN Planning
11.6 Comparisons
11.7 Extensions
11.8 Extended Goals
11.9 Discussion and Historical Remarks
11.10 Exercises
Chapter 12. Control Strategies in Deductive Planning
12.1 Introduction
12.2 Situation Calculus
12.3 Dynamic Logic
12.4 Discussion and Historical Remarks
12.5 Exercises
Part IV: Planning with Time and Resources
Chapter 13. Time for Planning
13.1 Introduction
13.2 Temporal References and Relations
13.3 Qualitative Temporal Relations
13.4 Quantitative Temporal Constraints
13.5 Discussion and Historical Remarks
13.6 Exercises
Chapter 14. Temporal Planning
14.1 Introduction
14.2 Planning with Temporal Operators
14.3 Planning with Chronicles
14.4 Discussion and Historical Remarks
14.5 Exercises
Chapter 15. Planning and Resource Scheduling
15.1 Introduction
15.2 Elements of Scheduling Problems
15.3 Machine Scheduling Problems
15.4 Integrating Planning and Scheduling
15.5 Discussion and Historical Remarks
15.6 Exercises
Part V: Planning under Uncertainty
Chapter 16. Planning Based on Markov Decision Processes
16.1 Introduction
16.2 Planning in Fully Observable Domains
16.3 Planning under Partial Observability
16.4 Reachability and Extended Goals
16.5 Discussion and Historical Remarks
16.6 Exercises
Chapter 17. Planning Based on Model Checking
17.1 Introduction
17.2 Planning for Reachability Goals
17.3 Planning for Extended Goals
17.4 Planning under Partial Observability
17.5 Planning as Model Checking versus MDPs
17.6 Discussion and Historical Remarks
17.7 Exercises
Chapter 18. Uncertainty with Neoclassical Techniques
18.1 Introduction
18.2 Planning as Satisfiability
18.3 Planning Graphs
18.4 Discussion and Historical Remarks
18.5 Exercises
Part VI: Case Studies and Applications
Chapter 19. Space Applications
19.1 Introduction
19.2 Deep Space 1
19.3 The Autonomous Remote Agent
19.4 The Remote Agent Architecture
19.5 The Planner Architecture
19.6 The Deep Space 1 Experiment
19.7 Discussion and Historical Remarks
Chapter 20. Planning in Robotics
20.1 Introduction
20.2 Path and Motion Planning
20.3 Planning for the Design of a Robust Controller
20.4 Dock-Worker Robots
20.5 Discussion and Historical Remarks
Chapter 21. Planning for Manufacturability Analysis
21.1 Introduction
21.2 Machined Parts
21.3 Feature Extraction
21.4 Generating Abstract Plans
21.5 Resolving Goal Interactions
21.6 Additional Steps
21.7 Operation Plan Evaluation
21.8 Efficiency Considerations
21.9 Concluding Remarks
Chapter 22. Emergency Evacuation Planning
22.1 Introduction
22.2 Evacuation Operations
22.3 Knowledge Representation
22.4 Hierarchical Task Editor
22.5 SiN
22.6 Example
22.7 Summary
22.8 Discussion and Historical Remarks
Chapter 23. Planning in the Game of Bridge
23.1 Introduction
23.2 Overview of Bridge
23.3 Game-Tree Search in Bridge
23.4 Adapting HTN Planning for Bridge
23.5 Implementation and Results
Part VII: Conclusion
Chapter 24. Other Approaches to Planning
24.1 Case-Based Planning
24.2 Linear and Integer Programming
24.3 Multiagent Planning
24.4 Plan Merging and Plan Rewriting
24.5 Abstraction Hierarchies
24.6 Domain Analysis
24.7 Planning and Learning
24.8 Planning and Acting, Situated Planning, and Dynamic Planning
24.9 Plan Recognition
24.10 Suggestions for Future Work
Part VIII: Appendices
Appendix A. Search Procedures and Computational Complexity
A.1 Nondeterministic Problem Solving
A.2 State-Space Search
A.3 Problem-Reduction Search
A.4 Computational Complexity of Procedures
A.5 Computational Complexity of Problems
A.6 Planning Domains as Language-Recognition Problems
A.7 Discussion and Historical Remarks
Appendix B. First-Order Logic
B.1 Introduction
B.2 Propositional Logic
B.3 First-Order Logic
Appendix C. Model Checking
C.1 Introduction
C.2 Intuitions
C.3 The Model Checking Problem
C.4 Model Checking Algorithms
C.5 Symbolic Model Checking
C.6 BDD-Based Symbolic Model Checking
automated planning theory and practice pdf
automated planning theory and practice
automated planning theory & practice
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automated planning and acting
Tags: Malik Ghallab, Dana Nau, Paolo Traverso, Automated Planning
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