Automated planning: theory and practice
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| 1. Verfasser: | |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam [u.a.]
Elsevier Morgan Kaufmann
2004
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| Schlagworte: | |
| Online-Zugang: | Table of contents Publisher description Inhaltsverzeichnis |
| Beschreibung: | Hier auch später erschienene, unveränderte Nachdrucke Includes bibliographical references (p. 573-607) and index |
| Beschreibung: | XXVIII, 635 S. Ill. 25 cm |
| ISBN: | 1558608567 |
Internformat
MARC
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| 084 | |a DAT 060f |2 stub | ||
| 100 | 1 | |a Ghallab, Malik |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Automated planning |b theory and practice |c Malik Ghallab ; Dana Nau ; Paolo Traverso |
| 264 | 1 | |a Amsterdam [u.a.] |b Elsevier Morgan Kaufmann |c 2004 | |
| 300 | |a XXVIII, 635 S. |b Ill. |c 25 cm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Hier auch später erschienene, unveränderte Nachdrucke | ||
| 500 | |a Includes bibliographical references (p. 573-607) and index | ||
| 650 | 7 | |a Planejamento da produção |2 larpcal | |
| 650 | 7 | |a Processamento de dados |2 larpcal | |
| 650 | 4 | |a Datenverarbeitung | |
| 650 | 4 | |a Production planning |x Data processing | |
| 650 | 0 | 7 | |a Automatische Handlungsplanung |0 (DE-588)4211191-2 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Automatische Handlungsplanung |0 (DE-588)4211191-2 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Nau, Dana S. |e Sonstige |4 oth | |
| 700 | 1 | |a Traverso, Paolo |e Sonstige |4 oth | |
| 856 | 4 | |u http://www.loc.gov/catdir/toc/els051/2003064381.html |3 Table of contents | |
| 856 | 4 | |u http://www.loc.gov/catdir/description/els051/2003064381.html |3 Publisher description | |
| 856 | 4 | 2 | |m Digitalisierung UB Augsburg |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014748106&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-014748106 | ||
Datensatz im Suchindex
| _version_ | 1804135278598684672 |
|---|---|
| adam_text | Contents
About the Authors
ii
Foreword
xxi
Preface
xxiii
Table of Notation
xxvii
Chapter
1
Introduction and Overview
1
1.1
First Intuitions on Planning
1
1.2
Forms of Planning
2
1.3
Domain-Independent Planning
3
1.4
Conceptual Model for Planning
5
1.5
Restricted Model
9
1.6
Extended Models
11
1.7
A Running Example: Dock-Worker Robots
13
Part I
Classical Planning
17
Chapter
2
Representations for Classical Planning
19
2.1
Introduction
19
2.2
Set-Theoretic Representation
20
2.2.1
Planning Domains, Problems, and Solutions
20
2.2.2
State Reachability
22
vii
viii Contents
2.2.3
Stating a Planning Problem
23
2.2.4
Properties of the Set-Theoretic Representation
24
2.3
Classical Representation
27
2.3.1
States
27
2.3.2
Operators and Actions
28
2.3.3
Plans, Problems, and Solutions
31
2.3.4
Semantics of Classical Representations
33
2.4
Extending the Classical Representation
34
2.4.1
Simple Syntactical Extensions
34
2.4.2
Conditional Planning Operators
34
2.4.3
Quantified Expressions
36
2.4.4
Disjunctive Preconditions
37
2.4.5
Axiomatic Inference
38
2.4.6
Function Symbols
39
2.4.7
Attached Procedures
39
2.4.8
Extended Goals
39
2.5
State-Variable Representation
41
2.5.1 State Variables
41
2.5.2
Operators and Actions
43
2.5.3
Domains and Problems
44
2.5.4
Properties
46
2.6
Comparisons
47
2.7
Discussion and Historical Remarks
49
2.8
Exercises
50
Chapter
3
Complexity of Classical Planning
55
3.1
Introduction
55
3.2
Preliminaries
56
3.3
Decidability and Undecidability Results
57
3.4
Complexity Results
59
3.4.1
Binary Counters
60
3.4.2
Unrestricted Classical Planning
61
3.4.3
Other Results
63
3.5
Limitations
65
3.6
Discussion and Historical Remarks
66
3.7
Exercises
66
Contents ix
69
69
69
73
76
78
81
81
85
85
86
91
94
100
101
103
105
Part II
Neoclassîcal Planning m
Chapter
6
Planning-Graph Techniques
113
Chapter
4
State-Space
Planning
4.1
Introduction
4.2
Forward Search
4.2.1
Formal Properties
70
4.2.2
Deterministic Implementations
72
4-3
Backward Search
4-4
The STRIPS Algorithm
4-5
Domain-Specific State-Space Planning
4.5.1
The Container-Stacking Domain
78
, 4.5.2
Planning Algorithm
79
4.6
Discussion and Historical Remarks
4-7
Exercises
Chapter
5
Plan-Space
Planning
5-і
Introduction
5.2
The Search Space of Partial Plans
5-3
Solution Plans
5-4
Algorithms for Plan-Space Planning
5.4.1
The
PSP
Procedure
94
5.4.2
The PoP Procedure
99
5.5
Extensions
5.6
•
Plan-Space versus State-Space Planning
5-7
Discussion and Historical Remarks
5.8
Exercises
Contents
6.1
Introduction
113
6.2
Planning
Graphs
114
6.2.1
Reachability Trees
114
6.2.2
Reachability with Planning Graphs
117
. 6.2.3
Independent Actions and Layered Plans
119
6.2.4
Mutual Exclusion Relations
120
6.3
The
Graphplan
Planner
123
6.3.1 Expanding the Planning Graph
123
6.3.2
Searching the Planning Graph
125
6.3.3
Analysis of
Graphplan 129
6.4
Extensions and Improvements of
Graphplan 131
6.4.1
Extending the Language
131
6.4.2
Improving the Planner
133
6.4.3
Extending the Independence Relation
134
6.5
Discussion and Historical Remarks
137
6.6
Exercises
139
Chapter
7
Propositional Satisfiability Techniques
143
7.1
Introduction
143
7.2
Planning Problems as Satisfiability Problems
144
7.2.1
States as Propositional Formulas
144
7.2.2
State Transitions as Propositional Formulas
145
7.2.3
Planning Problems as Propositional Formulas
147
7.3
Planning by Satisfiability
151
7.3.1
Davis-Putnam Procedure
152
7.3.2
Stochastic Procedures
156
7.4
Different Encodings
160
7.4.1
Action Representation
161
7.4.2
Frame Axioms
162
7.5
Discussion and Historical Remarks
164
7.6
Exercises
165
Contents xi
Chapter
8
Constraint Satisfaction Techniques
167
8.1
Introduction
167
8.2
Constraint Satisfaction Problems
168
8.3
Planning Problems as CSPs
172
8.3.1
Encoding a Planning Problem into a C5P
174
8.3.2
Analysis of the CSP Encoding
177
8.4
CSP Techniques and Algorithms
178
8.4.1
Search Algorithms for CSPs
178
8.4.2
Filtering Techniques
180
8.4.3
Local Search Techniques and Hybrid Approaches
184
8.5
Extended CSP Models
185
8.5.1
Active CSPs
185
8.5.2
Valued CSPs
187
8.6
CSP Techniques in Planning
187
8.6.1
CSPs in Plan-Space Search
187
8.6.2
CSPs for Planning-Graph Techniques
188
8.7
Discussion and Historical Remarks
189
8.8
Exercises
190
Part III
Heuristics and Control Strategies
193
Chapter
9
Heuristics in Planning
199
9.1
Introduction
199
9.2
Design Principle for Heuristics: Relaxation
199
9.3
Heuristics for State-Space Planning
201
9.3.1
State Reachability Relaxation
201
9.3.2
Heuristically Guided Backward Search
204
9.3.3
Admissible State-Space Heuristics
205
9.3.4 Graphplan
as a Heuristic Search Planner
207
9-4
Heuristics for Plan-Space Planning
208
9.4.1
Flaw-Selection Heuristics
208
9.4.2
Resolver-Selection Heuristics
212
9.5
Discussion and Historical Remarks
213
9-6
Exercises
214
Chapter
10
Control Rules in Planning
217
10.1
Introduction
217
10.2
Simple Temporal Logic
218
10.3 Progression
220
10.4 Planning Procedure
222
10.5 Extensions
223
10.6
Extended Goals
224
226
227
229
229
231
238
240
244
10.7
Discussion and Historical Remarks
10.8
Exercises
Chapter
11
Hierarchical Task Network Planning
11.1
Introduction
11.2
STN Planning
11.2.1
Tasks and Methods
231
11.2.2
Problems and Solutions
235
11.3
Total-Order STN Planning
11.4
Partial-Order STN Planning
11.5
HTN Planning
II.5.1 Task Networks
244
11.5.2
HTN Methods
245
11.5.3
HTN Problems and Solutions
247
11.5.4
Planning Procedures
248
11.6
Comparisons
11.6.1
HTN Planning versus STN Planning
250
11.6.2
HTN Methods versus Control Rules
251
11.7
Extensions
250
252
Contents xiii
11.7-1
Extensions from Chapter
2 252
II.7.2 Additional Extensions
255
11.8
Extended Goals
256
11.9
Discussion and Historical Remarks
257
11.1,0
Exercises
259
Chapter
12
Control Strategies in Deductive Planning
263
12.1
Introduction
263
12.2
Situation Calculus
264
12.2.1
Situations
264
12.2.2
Actions
265
12.2.3
Planning Domains, Problems, and Solutions
267
12.2.4
Plans as Programs in Situation Calculus
269
12.3
Dynamic Logic
270
12.3.1
The Language of the Logic
271
12.3.2
The Semantics
272
12.3.3
The Deductive Machinery
273
12.3.4
Planning Domains, Problems, and Solutions
273
12.3.5
Extensions
274
12.3.6
User-Defined Control Strategies as Tactics
275
12.4
Discussion and Historical Remarks
276
12.5
Exercises
278
Part IV
Planning with Time and Resources 281
Chapter
13
Time for Planning
285
13-І
Introduction
285
13.2
Temporal References and Relations
285
13.3
Qualitative Temporal Relations
290
xiv Contents
13.3.1 Point Algebra 290
13.3.2
Interval
Algebra 293
!3·3·3
A Geometric
Interpretation
of Interval Algebra
299
13.3.4
Interval Algebra versus Point Algebra
301
13.4
Quantitative Temporal Constraints
302
13.4.1
Simple Temporal Constraints
303
13.4.2
Temporal Constraint Networks
305
13.5
Discussion and Historical Remarks
306
13.6
Exercises
307
Chapter
14
Temporal Planning
309
14.1 Introduction
309
14.2
Planning with Temporal Operators
310
14.2.1
Temporal Expressions and Temporal Databases
310
14.2.2
Temporal Planning Operators
314
14.2.3
Domain Axioms
317
14.2.4
Temporal Planning Domains, Problems, and Plans
320
14.2.5
Concurrent Actions with Interfering Effects
321
14.2.6
A Temporal Planning Procedure
323
14.3
Planning with Chronicles
326
14.3.1
State Variables, Timelines, and Chronicles
327
14.3.2
Chronicles as Planning Operators
334
14.3.3
Chronicle Planning Procedures
336
14.3.4
Constraint Management in CP
339
14.3.5
Search Control in CP
341
14.4
Discussion and Historical Remarks
343
14.5
Exercises
345
Chapter I5
Planning and Resource Scheduling
349
15.1
Introduction
349
15.2
Elements of Scheduling Problems
351
15.2.1
Actions
352
15.2.2
Resources
352
15.2.3
Constraints and Cost Functions
354
Contents xv
15.3 Machine
Scheduling Problems
356
15.3.1
Classes of Machine Scheduling Problems
356
15.3.2
Complexity of Machine Scheduling
358
15.3.3
Solving Machine Scheduling Problems
360
15.3.4
Planning and Machine Scheduling
360
15.4
Integrating Planning and Scheduling
362
15.4.1
Representation
362
15.4.2
Detecting Resource Conflicts
367
15.4.3
Managing Resource Conflict Flaws
370
15.5
Discussion and Historical Remarks
372
15.6
Exercises
373
Part V
Planning under Uncertainty
375
Chapter l6
Planning Based on Markov Decision Processes
379
16.1 Introduction
379
16.2
Planning in Fully Observable Domains
380
16.2.1
Domains, Plans, and Planning Problems
380
16.2.2
Planning Algorithms
386
16.3
Planning under Partial Observability
392
16.3.1
Domains, Plans, and Planning Problems
392
16.3.2
Planning Algorithms
396
16.4
Reachability and Extended Goals
397
16.5
Discussion and Historical Remarks
398
16.6
Exercises
400
Chapter
17
Planning Based on Model Checking
403
17.1
Introduction
403
17.2
Planning for Reachability Goals
404
xvi Contents
17.2.1 Domains, Plans, and
Planning
Problems 405
17.2.2
Planning
Algorithms
408
17.3
Planning for Extended Goals
414
17.3.1
Domains, Plans, and Planning Problems
414
17.3.2
Planning Algorithms
418
17.3.3
Beyond Temporal Logic
421
17.4
Planning under Partial Observability
425
17.4.1
Domains, Plans, and Planning Problems
425
17.4.2
Planning Algorithms
429
17.5
Planning as Model Checking versus MDPs
432
17.6
Discussion and Historical Remarks
432
17.7
Exercises
434
Chapter l8
Uncertainty with Neoclassical Techniques
437
18.1 Introduction
437
18.2
Planning as Satisfiability
437
18.2.1
Planning Problems
438
18.2.2
Planning Problems as Propositional Formulas
439
18.2.3
Planning by Satisfiability
442
18.2.4
QBF Planning
442
18.3
Planning Graphs
443
18.4
Discussion and Historical Remarks
446
18.5
Exercises
447
Part VI
Case Studies and Applications
449
Chapter
19
Space Applications
451
19.1
Introduction
451
19.2
Deep Space
1 451
Contents xvii
19·3
The Autonomous
Remote Agent 451
19.4
The Remote Agent Architecture
453
19.5
The Planner Architecture
457
19.6
The Deep Space
1
Experiment
461
19.6.1
Validation Objectives
462
19.6.2
Scenarios
463
19.6.3
Experiment Results
464
19.6.4
Lessons Learned
466
19.7
Discussion and Historical Remarks
466
Chapter
20
Planning in Robotics
469
20.1
Introduction
469
20.2
Path and Motion Planning
471
20.3
Planning for the Design of a Robust Controller
477
20.3.1
Sensory-Motor Functions
478
20.3.2
Modalities
480
20.3.3
Tne Controller
483
20.3.4
Analysis of the Approach
487
20.4
Dock-Worker Robots
487
20.5
Discussion and Historical Remarks
490
Chapter
21
Planning for Manufacturability Analysis
493
21.1
Introduction
493
21.2
Machined Parts
493
21.3
Feature Extraction
495
21.4
Generating Abstract Plans
497
21.5
Resolving Goal Interactions
499
21.6
Additional Steps
499
21.7
Operation Plan Evaluation
502
21.8
Efficiency Considerations
502
21.9
Concluding Remarks
503
xviii Contents
Chapter
22
Emergency Evacuation Planning
505
22.1
Introduction
22.2
Evacuation Operations
22.3
Knowledge Representation
22.3.1
HTNs
507
22.3.2
Cases
508
22.4
Hierarchical Task Editor
22.5
SiN
22.5.I How SiN Works
509
22.5.2
Correctness of SiN
511
22.5.3
Imperfect World Information
22.6
Example
22.7
Summary
22.8
Discussion and Historical Remarks
505
506
507
508
509
511
512
513
515
Chapter
23
Planning in the Game of Bridge
517
23.1 Introduction
517
23.2
Overview of Bridge
517
23.3
Game-Tree Search in Bridge
519
23.4
Adapting HTN Planning for Bridge
521
23.5
Implementation and Results
524
Part
VII
Conclusion
525
Chapter
24
Other Approaches to Planning
527
24.1 Case-Based Planning
527
24.2
Linear and Integer Programming
529
Contents xix
24.3 Multiagent
Planning
530
24.4 Plan
Merging and Plan Rewriting
531
24.5
Abstraction Hierarchies
532
24.6
Domain Analysis
534
24.7
Planning and Learning
535
24.8
Planning and Acting, Situated Planning,
and Dynamic Planning
536
24.9
Plan Recognition
537
24.10 Suggestions for Future Work
540
Part
VIII
Appendices
541
Appendix A
Search Procedures and Computational Complexity
543
A.I Nondeterministk Problem Solving
543
A.2 State-Space Search
544
A.3 Problem-Reduction Search
548
A.4 Computational Complexity of Procedures
550
A.5 Computational Complexity of Problems
551
A.6 Planning Domains as Language-Recognition Problems
552
A.
7
Discussion and Historical Remarks
553
Appendix
В
First-Order Logic
555
B.I Introduction
555
B.2 Propositional Logic
555
B.3 First-Order Logic
557
xx Contents
Appendix
С
Model
Checking
561
C.I Introduction
561
С.
2
Intuitions
561
С.З
The Model Checking Problem
563
C.4 Model Checking Algorithms
565
C.5 Symbolic Model Checking
567
C.6 BDD-Based Symbolic Model Checking
570
Bibliography
573
Index
609
|
| adam_txt |
Contents
About the Authors
ii
Foreword
xxi
Preface
xxiii
Table of Notation
xxvii
Chapter
1
Introduction and Overview
1
1.1
First Intuitions on Planning
1
1.2
Forms of Planning
2
1.3
Domain-Independent Planning
3
1.4
Conceptual Model for Planning
5
1.5
Restricted Model
9
1.6
Extended Models
11
1.7
A Running Example: Dock-Worker Robots
13
Part I
Classical Planning
17
Chapter
2
Representations for Classical Planning
19
2.1
Introduction
19
2.2
Set-Theoretic Representation
20
2.2.1
Planning Domains, Problems, and Solutions
20
2.2.2
State Reachability
22
vii
viii Contents
2.2.3
Stating a Planning Problem
23
2.2.4
Properties of the Set-Theoretic Representation
24
2.3
Classical Representation
27
2.3.1
States
27
2.3.2
Operators and Actions
28
2.3.3
Plans, Problems, and Solutions
31
2.3.4
Semantics of Classical Representations
33
2.4
Extending the Classical Representation
34
2.4.1
Simple Syntactical Extensions
34
2.4.2
Conditional Planning Operators
34
2.4.3
Quantified Expressions
36
2.4.4
Disjunctive Preconditions
37
2.4.5
Axiomatic Inference
38
2.4.6
Function Symbols
39
2.4.7
Attached Procedures
39
2.4.8
Extended Goals
39
2.5
State-Variable Representation
41
2.5.1 State Variables
41
2.5.2
Operators and Actions
43
2.5.3
Domains and Problems
44
2.5.4
Properties
46
2.6
Comparisons
47
2.7
Discussion and Historical Remarks
49
2.8
Exercises
50
Chapter
3
Complexity of Classical Planning
55
3.1
Introduction
55
3.2
Preliminaries
56
3.3
Decidability and Undecidability Results
57
3.4
Complexity Results
59
3.4.1
Binary Counters
60
3.4.2
Unrestricted Classical Planning
61
3.4.3
Other Results
63
3.5
Limitations
65
3.6
Discussion and Historical Remarks
66
3.7
Exercises
66
Contents ix
69
69
69
73
76
78
81
81
85
85
86
91
94
100
101
103
105
Part II
Neoclassîcal Planning m
Chapter
6
Planning-Graph Techniques
113
Chapter
4
State-Space
Planning
4.1
Introduction
4.2
Forward Search
4.2.1
Formal Properties
70
4.2.2
Deterministic Implementations
72
4-3
Backward Search
4-4
The STRIPS Algorithm
4-5
Domain-Specific State-Space Planning
4.5.1
The Container-Stacking Domain
78
, 4.5.2
Planning Algorithm
79
4.6
Discussion and Historical Remarks
4-7
Exercises
Chapter
5
Plan-Space
Planning
5-і
Introduction
5.2
The Search Space of Partial Plans
5-3
Solution Plans
5-4
Algorithms for Plan-Space Planning
5.4.1
The
PSP
Procedure
94
5.4.2
The PoP Procedure
99
5.5
Extensions
5.6
•
Plan-Space versus State-Space Planning
5-7
Discussion and Historical Remarks
5.8
Exercises
Contents
6.1
Introduction
113
6.2
Planning
Graphs
114
6.2.1
Reachability Trees
114
6.2.2
Reachability with Planning Graphs
117
. 6.2.3
Independent Actions and Layered Plans
119
6.2.4
Mutual Exclusion Relations
120
6.3
The
Graphplan
Planner
123
6.3.1 Expanding the Planning Graph
123
6.3.2
Searching the Planning Graph
125
6.3.3
Analysis of
Graphplan 129
6.4
Extensions and Improvements of
Graphplan 131
6.4.1
Extending the Language
131
6.4.2
Improving the Planner
133
6.4.3
Extending the Independence Relation
134
6.5
Discussion and Historical Remarks
137
6.6
Exercises
139
Chapter
7
Propositional Satisfiability Techniques
143
7.1
Introduction
143
7.2
Planning Problems as Satisfiability Problems
144
7.2.1
States as Propositional Formulas
144
7.2.2
State Transitions as Propositional Formulas
145
7.2.3
Planning Problems as Propositional Formulas
147
7.3
Planning by Satisfiability
151
7.3.1
Davis-Putnam Procedure
152
7.3.2
Stochastic Procedures
156
7.4
Different Encodings
160
7.4.1
Action Representation
161
7.4.2
Frame Axioms
162
7.5
Discussion and Historical Remarks
164
7.6
Exercises
165
Contents xi
Chapter
8
Constraint Satisfaction Techniques
167
8.1
Introduction
167
8.2
Constraint Satisfaction Problems
168
8.3
Planning Problems as CSPs
172
8.3.1
Encoding a Planning Problem into a C5P
174
8.3.2
Analysis of the CSP Encoding
177
8.4
CSP Techniques and Algorithms
178
8.4.1
Search Algorithms for CSPs
178
8.4.2
Filtering Techniques
180
8.4.3
Local Search Techniques and Hybrid Approaches
184
8.5
Extended CSP Models
185
8.5.1
Active CSPs
185
8.5.2
Valued CSPs
187
8.6
CSP Techniques in Planning
187
8.6.1
CSPs in Plan-Space Search
187
8.6.2
CSPs for Planning-Graph Techniques
188
8.7
Discussion and Historical Remarks
189
8.8
Exercises
190
Part III
Heuristics and Control Strategies
193
Chapter
9
Heuristics in Planning
199
9.1
Introduction
199
9.2
Design Principle for Heuristics: Relaxation
199
9.3
Heuristics for State-Space Planning
201
9.3.1
State Reachability Relaxation
201
9.3.2
Heuristically Guided Backward Search
204
9.3.3
Admissible State-Space Heuristics
205
9.3.4 Graphplan
as a Heuristic Search Planner
207
9-4
Heuristics for Plan-Space Planning
208
9.4.1
Flaw-Selection Heuristics
208
9.4.2
Resolver-Selection Heuristics
212
9.5
Discussion and Historical Remarks
213
9-6
Exercises
214
Chapter
10
Control Rules in Planning
217
10.1
Introduction
217
10.2
Simple Temporal Logic
218
10.3 Progression
220
10.4 Planning Procedure
222
10.5 Extensions
223
10.6
Extended Goals
224
226
227
229
229
231
238
240
244
10.7
Discussion and Historical Remarks
10.8
Exercises
Chapter
11
Hierarchical Task Network Planning
11.1
Introduction
11.2
STN Planning
11.2.1
Tasks and Methods
231
11.2.2
Problems and Solutions
235
11.3
Total-Order STN Planning
11.4
Partial-Order STN Planning
11.5
HTN Planning
II.5.1 Task Networks
244
11.5.2
HTN Methods
245
11.5.3
HTN Problems and Solutions
247
11.5.4
Planning Procedures
248
11.6
Comparisons
11.6.1
HTN Planning versus STN Planning
250
11.6.2
HTN Methods versus Control Rules
251
11.7
Extensions
250
252
Contents xiii
11.7-1
Extensions from Chapter
2 252
II.7.2 Additional Extensions
255
11.8
Extended Goals
256
11.9
Discussion and Historical Remarks
257
11.1,0
Exercises
259
Chapter
12
Control Strategies in Deductive Planning
263
12.1
Introduction
263
12.2
Situation Calculus
264
12.2.1
Situations
264
12.2.2
Actions
265
12.2.3
Planning Domains, Problems, and Solutions
267
12.2.4
Plans as Programs in Situation Calculus
269
12.3
Dynamic Logic
270
12.3.1
The Language of the Logic
271
12.3.2
The Semantics
272
12.3.3
The Deductive Machinery
273
12.3.4
Planning Domains, Problems, and Solutions
273
12.3.5
Extensions
274
12.3.6
User-Defined Control Strategies as Tactics
275
12.4
Discussion and Historical Remarks
276
12.5
Exercises
278
Part IV
Planning with Time and Resources 281
Chapter
13
Time for Planning
285
13-І
Introduction
285
13.2
Temporal References and Relations
285
13.3
Qualitative Temporal Relations
290
xiv Contents
13.3.1 Point Algebra 290
13.3.2
Interval
Algebra 293
!3·3·3
A Geometric
Interpretation
of Interval Algebra
299
13.3.4
Interval Algebra versus Point Algebra
301
13.4
Quantitative Temporal Constraints
302
13.4.1
Simple Temporal Constraints
303
13.4.2
Temporal Constraint Networks
305
13.5
Discussion and Historical Remarks
306
13.6
Exercises
307
Chapter
14
Temporal Planning
309
14.1 Introduction
309
14.2
Planning with Temporal Operators
310
14.2.1
Temporal Expressions and Temporal Databases
310
14.2.2
Temporal Planning Operators
314
14.2.3
Domain Axioms
317
14.2.4
Temporal Planning Domains, Problems, and Plans
320
14.2.5
Concurrent Actions with Interfering Effects
321
14.2.6
A Temporal Planning Procedure
323
14.3
Planning with Chronicles
326
14.3.1
State Variables, Timelines, and Chronicles
327
14.3.2
Chronicles as Planning Operators
334
14.3.3
Chronicle Planning Procedures
336
14.3.4
Constraint Management in CP
339
14.3.5
Search Control in CP
341
14.4
Discussion and Historical Remarks
343
14.5
Exercises
345
Chapter I5
Planning and Resource Scheduling
349
15.1
Introduction
349
15.2
Elements of Scheduling Problems
351
15.2.1
Actions
352
15.2.2
Resources
352
15.2.3
Constraints and Cost Functions
354
Contents xv
15.3 Machine
Scheduling Problems
356
15.3.1
Classes of Machine Scheduling Problems
356
15.3.2
Complexity of Machine Scheduling
358
15.3.3
Solving Machine Scheduling Problems
360
15.3.4
Planning and Machine Scheduling
360
15.4
Integrating Planning and Scheduling
362
15.4.1
Representation
362
15.4.2
Detecting Resource Conflicts
367
15.4.3
Managing Resource Conflict Flaws
370
15.5
Discussion and Historical Remarks
372
15.6
Exercises
373
Part V
Planning under Uncertainty
375
Chapter l6
Planning Based on Markov Decision Processes
379
16.1 Introduction
379
16.2
Planning in Fully Observable Domains
380
16.2.1
Domains, Plans, and Planning Problems
380
16.2.2
Planning Algorithms
386
16.3
Planning under Partial Observability
392
16.3.1
Domains, Plans, and Planning Problems
392
16.3.2
Planning Algorithms
396
16.4
Reachability and Extended Goals
397
16.5
Discussion and Historical Remarks
398
16.6
Exercises
400
Chapter
17
Planning Based on Model Checking
403
17.1
Introduction
403
17.2
Planning for Reachability Goals
404
xvi Contents
17.2.1 Domains, Plans, and
Planning
Problems 405
17.2.2
Planning
Algorithms
408
17.3
Planning for Extended Goals
414
17.3.1
Domains, Plans, and Planning Problems
414
17.3.2
Planning Algorithms
418
17.3.3
Beyond Temporal Logic
421
17.4
Planning under Partial Observability
425
17.4.1
Domains, Plans, and Planning Problems
425
17.4.2
Planning Algorithms
429
17.5
Planning as Model Checking versus MDPs
432
17.6
Discussion and Historical Remarks
432
17.7
Exercises
434
Chapter l8
Uncertainty with Neoclassical Techniques
437
18.1 Introduction
437
18.2
Planning as Satisfiability
437
18.2.1
Planning Problems
438
18.2.2
Planning Problems as Propositional Formulas
439
18.2.3
Planning by Satisfiability
442
18.2.4
QBF Planning
442
18.3
Planning Graphs
443
18.4
Discussion and Historical Remarks
446
18.5
Exercises
447
Part VI
Case Studies and Applications
449
Chapter
19
Space Applications
451
19.1
Introduction
451
19.2
Deep Space
1 451
Contents xvii
19·3
The Autonomous
Remote Agent 451
19.4
The Remote Agent Architecture
453
19.5
The Planner Architecture
457
19.6
The Deep Space
1
Experiment
461
19.6.1
Validation Objectives
462
19.6.2
Scenarios
463
19.6.3
Experiment Results
464
19.6.4
Lessons Learned
466
19.7
Discussion and Historical Remarks
466
Chapter
20
Planning in Robotics
469
20.1
Introduction
469
20.2
Path and Motion Planning
471
20.3
Planning for the Design of a Robust Controller
477
20.3.1
Sensory-Motor Functions
478
20.3.2
Modalities
480
20.3.3
Tne Controller
483
20.3.4
Analysis of the Approach
487
20.4
Dock-Worker Robots
487
20.5
Discussion and Historical Remarks
490
Chapter
21
Planning for Manufacturability Analysis
493
21.1
Introduction
493
21.2
Machined Parts
493
21.3
Feature Extraction
495
21.4
Generating Abstract Plans
497
21.5
Resolving Goal Interactions
499
21.6
Additional Steps
499
21.7
Operation Plan Evaluation
502
21.8
Efficiency Considerations
502
21.9
Concluding Remarks
503
xviii Contents
Chapter
22
Emergency Evacuation Planning
505
22.1
Introduction
22.2
Evacuation Operations
22.3
Knowledge Representation
22.3.1
HTNs
507
22.3.2
Cases
508
22.4
Hierarchical Task Editor
22.5
SiN
22.5.I How SiN Works
509
22.5.2
Correctness of SiN
511
22.5.3
Imperfect World Information
22.6
Example
22.7
Summary
22.8
Discussion and Historical Remarks
505
506
507
508
509
511
512
513
515
Chapter
23
Planning in the Game of Bridge
517
23.1 Introduction
517
23.2
Overview of Bridge
517
23.3
Game-Tree Search in Bridge
519
23.4
Adapting HTN Planning for Bridge
521
23.5
Implementation and Results
524
Part
VII
Conclusion
525
Chapter
24
Other Approaches to Planning
527
24.1 Case-Based Planning
527
24.2
Linear and Integer Programming
529
Contents xix
24.3 Multiagent
Planning
530
24.4 Plan
Merging and Plan Rewriting
531
24.5
Abstraction Hierarchies
532
24.6
Domain Analysis
534
24.7
Planning and Learning
535
24.8
Planning and Acting, Situated Planning,
and Dynamic Planning
536
24.9
Plan Recognition
537
24.10 Suggestions for Future Work
540
Part
VIII
Appendices
541
Appendix A
Search Procedures and Computational Complexity
543
A.I Nondeterministk Problem Solving
543
A.2 State-Space Search
544
A.3 Problem-Reduction Search
548
A.4 Computational Complexity of Procedures
550
A.5 Computational Complexity of Problems
551
A.6 Planning Domains as Language-Recognition Problems
552
A.
7
Discussion and Historical Remarks
553
Appendix
В
First-Order Logic
555
B.I Introduction
555
B.2 Propositional Logic
555
B.3 First-Order Logic
557
xx Contents
Appendix
С
Model
Checking
561
C.I Introduction
561
С.
2
Intuitions
561
С.З
The Model Checking Problem
563
C.4 Model Checking Algorithms
565
C.5 Symbolic Model Checking
567
C.6 BDD-Based Symbolic Model Checking
570
Bibliography
573
Index
609 |
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| index_date | 2024-07-02T14:25:34Z |
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| institution | BVB |
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| language | English |
| lccn | 2003064381 |
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| spelling | Ghallab, Malik Verfasser aut Automated planning theory and practice Malik Ghallab ; Dana Nau ; Paolo Traverso Amsterdam [u.a.] Elsevier Morgan Kaufmann 2004 XXVIII, 635 S. Ill. 25 cm txt rdacontent n rdamedia nc rdacarrier Hier auch später erschienene, unveränderte Nachdrucke Includes bibliographical references (p. 573-607) and index Planejamento da produção larpcal Processamento de dados larpcal Datenverarbeitung Production planning Data processing Automatische Handlungsplanung (DE-588)4211191-2 gnd rswk-swf Automatische Handlungsplanung (DE-588)4211191-2 s DE-604 Nau, Dana S. Sonstige oth Traverso, Paolo Sonstige oth http://www.loc.gov/catdir/toc/els051/2003064381.html Table of contents http://www.loc.gov/catdir/description/els051/2003064381.html Publisher description Digitalisierung UB Augsburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014748106&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Ghallab, Malik Automated planning theory and practice Planejamento da produção larpcal Processamento de dados larpcal Datenverarbeitung Production planning Data processing Automatische Handlungsplanung (DE-588)4211191-2 gnd |
| subject_GND | (DE-588)4211191-2 |
| title | Automated planning theory and practice |
| title_auth | Automated planning theory and practice |
| title_exact_search | Automated planning theory and practice |
| title_exact_search_txtP | Automated planning theory and practice |
| title_full | Automated planning theory and practice Malik Ghallab ; Dana Nau ; Paolo Traverso |
| title_fullStr | Automated planning theory and practice Malik Ghallab ; Dana Nau ; Paolo Traverso |
| title_full_unstemmed | Automated planning theory and practice Malik Ghallab ; Dana Nau ; Paolo Traverso |
| title_short | Automated planning |
| title_sort | automated planning theory and practice |
| title_sub | theory and practice |
| topic | Planejamento da produção larpcal Processamento de dados larpcal Datenverarbeitung Production planning Data processing Automatische Handlungsplanung (DE-588)4211191-2 gnd |
| topic_facet | Planejamento da produção Processamento de dados Datenverarbeitung Production planning Data processing Automatische Handlungsplanung |
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