Prolog programming for artificial intelligence:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Harlow [u.a.]
Addison-Wesley
2012
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| Edition: | 4. ed. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XXI, 673 S. graph. Darst. |
| ISBN: | 9780321417466 |
Staff View
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Record in the Search Index
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|---|---|
| adam_text | Titel: Prolog programming for artificial intelligence
Autor: Bratko, Ivan
Jahr: 2012
Contents
Foreword (from Patrick Winston s Foreword to the Second Edition) xiii
Preface xvii
PART I The Prolog Language 1
1 Introduction to Prolog 3
1.1 Defining relations by facts 3
1.2 Defining relations by rules 8
1.3 Recursive rules 13
1.4 Running the program with a Prolog System 17
1.5 How Prolog answers questions 18
1.6 Declarative and procedura! meaning of programs 21
1.7 A robot s world - preview of things to come 22
1.8 Crosswords, maps and schedules 27
Summary 30
References 31
2 Syntax and Meaning of Prolog Programs 32
2.1 Data objects 32
2.2 Matching 39
2.3 Declarative meaning of Prolog programs 44
2.4 Procedural meaning 47
2.5 Order of clauses and goals 52
2.6 The relation between Prolog and logic 57
Summary 58
References 59
3 Lists, Operators, Arithmetic 60
3.1 Representation of lists 60
3.2 Some Operations on lists 62
3.3 Operator notation 74
3.4 Arithmetic 79
Summary 85
vi Contents
4 Programming Examples 86
4.1 Finding a path in a graph 86
4.2 Robot task planning 90
4.3 Trip planning 97
4.4 Solving cryptarithmetic problems 103
4.5 The eight-queens problem 105
4.6 WordNet ontology 115
Summary 124
5 Controlling Backtracking 126
5.1 Preventing backtracking 126
5.2 Examples of using cut 131
5.3 Negation as failure 135
5.4 Closed world assumption, and problems with cut and negation 138
Summary 142
References 142
6 Built-in Predicates 143
6.1 Testing the type of terms 143
6.2 Constructing and decomposing terms: = .., functor, arg, name 150
6.3 Various kinds of equality and comparison 155
6.4 Database manipulation 157
6.5 Control facilities 1ß0
6.6 bagof, setof and findall 161
6.7 Input and Output 164
Summary 175
Reference to Prolog Standard 176
7 Constraint Logic Programming 177
7.1 Constraint satisfaction and logic programming 177
7.2 CLP over real numbers: CLP(R), CLP(Q) 184
7.3 Examples of CLP(R) programming: blocks in boxes 188
7.4 CLP over finite domains: CLP(FD) 191
Summary 195
References 196
8 Programming Style and Technique 197
8.1 General principles of good programming 197
8.2 How to think about Prolog programs 1
8.3 Programming style 201
Contents VII
8.4 Debugging 204
8.5 Improving efficiency 206
Summary 219
References 220
9 Operations on Data Structures 221
9.1 Sorting lists 221
9.2 Representing sets by binary trees 225
9.3 Insertion and deletion in a binary dictionary 231
9.4 Displaying trees 235
9.5 Graphs 237
Summary 244
References 245
10 Balanced Trees 246
10.1 2-3 trees 246
10.2 AVL-trees: approximately balanced trees 253
Summary 256
References and historical notes 257
PART II Prolog in Artificial Intelligence 259
11 Problem-Solving as Search 261
11.1 Introductory concepts and examples 261
11.2 Depth-first search and iterative deepening 265
11.3 Breadth-first search 271
11.4 Analysis of basic search techniques 275
Summary 278
References 279
12 Heuristic Search and the A* Algorithm 280
12.1 Best-first search 280
12.2 Best-first search applied to the eight puzzle 289
12.3 Best-first search applied to scheduling 294
Summary 298
References and historical notes 299
13 Best-First Search: Minimizing Time and Space 301
13.1 Time and space complexity of the A* algorithm 301
13.2 IDA* - iterative deepening A* algorithm 302
VÜi Contents
13.3 RBFS - recursive best-first search 305
13.4 RTA* - real-time A* algorithm 311
Summary 316
References 317
14 Problem Decomposition and AND/OR Graphs 318
14.1 AND/OR graph representation of problems 318
14.2 Examples of AND/OR representation 322
14.3 Basic AND/OR search procedures 325
14.4 Best-first AND/OR search 330
Summary 341
References 342
15 Knowledge Representation and Expert Systems 343
15.1 Functions and structure of an expert System 343
15.2 Representing knowledge with if-then rules 345
15.3 Forward and backward chaining in rule-based Systems 348
15.4 Generating explanation 353
15.5 Introducing uncertainty 357
15.6 Semantic networks and frames 360
Summary 367
References 368
16 Probabilistic Reasoning with Bayesian Networks 370
16.1 Probabilities, beliefs and Bayesian networks 370
16.2 Some formulas from probability calculus 375
16.3 Probabilistic reasoning in Bayesian networks 376
16.4 d-separation 381
Summary 383
References 383
17 Planning 385
17.1 Representing actions 385
17.2 Deriving plans by means-ends analysis 388
17.3 Goal regression 393
17.4 Combining regression planning with best-first heuristic 396
17.5 Uninstantiated actions and goals 3
17.6 Partial order planning 401
Summary 403
References and historical notes 404
Contents ix
18 Partial Order Planning and GRAPHPLAN 406
18.1 Partial order planning 406
18.2 An implementation of partial order planning 410
18.3 GRAPHPLAN 417
18.4 Implementation of GRAPHPLAN 422
Summary 426
References and historical notes 427
19 Scheduling, Simulation and Control with CLP 429
19.1 Scheduling with CLP 429
19.2 A Simulation program with constraints 436
19.3 Simulation and control of dynamic Systems 440
Summary 445
20 Machine Learning 446
20.1 Introduction 446
20.2 The problem of learning concepts from examples 448
20.3 Learning relational descriptions: a detailed example 454
20.4 Learning simple if-then rules 459
20.5 Induction of decision trees 467
20.6 Learning from noisy data and tree pruning 474
20.7 Success of learning 481
Summary 483
References and notes on other approaches 485
21 Inductive Logic Programming 489
21.1 Introduction 489
21.2 Constructing Prolog programs from examples 492
21.3 Program HYPER 503
Summary 520
References and historical notes 520
22 Qualitative Reasoning 522
22.1 Common sense, qualitative reasoning and naive physics 522
22.2 Qualitative reasoning about static Systems 526
22.3 Qualitative reasoning about dynamic Systems 530
22.4 A qualitative Simulation program 536
22.5 Discussion of the qualitative Simulation program 546
Summary 550
References and historical notes 551
X Contents
23 Language Processing with Grammar Rules 554
23.1 Grammar rules in Prolog 554
23.2 Handling meaning 561
23.3 Defining the meaning of natural language 566
Summary 576
References 576
24 Game Playing 578
24.1 Two-person, perfect-information games 578
24.2 The minimax principle 580
24.3 The alpha-beta algorithm: an efficient implementation of minimax 582
24.4 Minimax-based programs: refinements and limitations 586
24.5 Pattern knowledge and the mechanism of advice 588
24.6 A chess endgame program in Advice Language 0 591
Summary 603
References and historical notes 603
25 Meta-Programming 606
25.1 Meta-programs and meta-interpreters 606
25.2 Prolog meta-interpreters 607
25.3 Top level interpreter for constraint logic programming 611
25.4 Abductive reasoning 612
25.5 Query-the-user interpreter 617
25.6 Explanation-based generalization 621
25.7 Pattern-directed programming and blackboard Systems 627
25.8 A simple theorem prover as a pattern-directed program 634
Summary 639
References 640
Appendix A Some Differences Between Prolog
Implementations 641
Appendix B Some Frequently Used Predicates 643
Solutions to Selected Exercises 646
Index 665
|
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| indexdate | 2024-07-09T21:41:57Z |
| institution | BVB |
| isbn | 9780321417466 |
| language | English |
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| spelling | Bratko, Ivan 1946- Verfasser (DE-588)174101619 aut Prolog programming for artificial intelligence Ivan Bratko 4. ed. Harlow [u.a.] Addison-Wesley 2012 XXI, 673 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf PROLOG Programmiersprache (DE-588)4047464-1 gnd rswk-swf PROLOG Programmiersprache (DE-588)4047464-1 s Künstliche Intelligenz (DE-588)4033447-8 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017684116&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Bratko, Ivan 1946- Prolog programming for artificial intelligence Künstliche Intelligenz (DE-588)4033447-8 gnd PROLOG Programmiersprache (DE-588)4047464-1 gnd |
| subject_GND | (DE-588)4033447-8 (DE-588)4047464-1 |
| title | Prolog programming for artificial intelligence |
| title_auth | Prolog programming for artificial intelligence |
| title_exact_search | Prolog programming for artificial intelligence |
| title_full | Prolog programming for artificial intelligence Ivan Bratko |
| title_fullStr | Prolog programming for artificial intelligence Ivan Bratko |
| title_full_unstemmed | Prolog programming for artificial intelligence Ivan Bratko |
| title_short | Prolog programming for artificial intelligence |
| title_sort | prolog programming for artificial intelligence |
| topic | Künstliche Intelligenz (DE-588)4033447-8 gnd PROLOG Programmiersprache (DE-588)4047464-1 gnd |
| topic_facet | Künstliche Intelligenz PROLOG Programmiersprache |
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