Paradigms of artificial intelligence programming: case studies in common LISP
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
San Mateo, Calif.
Morgan Kaufmann Publ.
1992
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| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Literaturverz S. [901] - 918 |
| Physical Description: | XXVIII, 946 S. graph. Darst. |
| ISBN: | 1558601910 |
Staff View
MARC
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| 100 | 1 | |a Norvig, Peter |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Paradigms of artificial intelligence programming |b case studies in common LISP |c Peter Norvig |
| 264 | 1 | |a San Mateo, Calif. |b Morgan Kaufmann Publ. |c 1992 | |
| 300 | |a XXVIII, 946 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Literaturverz S. [901] - 918 | ||
| 650 | 4 | |a Common Lisp (Langage de programmation) | |
| 650 | 7 | |a Inteligência artificial |2 larpcal | |
| 650 | 4 | |a Intelligence artificielle | |
| 650 | 7 | |a Kunstmatige intelligentie |2 gtt | |
| 650 | 7 | |a LISP |2 gtt | |
| 650 | 4 | |a Programmation (Informatique) | |
| 650 | 4 | |a Künstliche Intelligenz | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a COMMON LISP (Computer program language) | |
| 650 | 4 | |a Computer programming | |
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Record in the Search Index
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|---|---|
| adam_text | Contents
Preface vii
Why Lisp? Why Common Lisp? viii
Outline of the Book xi
How to Use This Book xiii
Supplementary Texts and Reference Books xiii
A Note on Exercises xv
Acknowledgments xv
PART I INTRODUCTION TO COMMON LISP 1
1 Introduction to Lisp 3
1 1 Symbolic Computation 6
1 2 Variables 8
1 3 Special Forms 9
1 4 Lists 10
1 5 Defining New Functions 12
1 6 Using Functions 14
1 7 Higher-Order Functions 18
1 8 Other Data Types 22
1 9 Summary: The Lisp Evaluation Rule 22
1 10 What Makes Lisp Different? 25
1 11 Exercises 31
1 12 Answers 32
xviii
CONTENTS
2 A Simple Lisp Program 34
21A Grammar for a Subset of English 35
22A Straightforward Solution 35
23A Rule-Based Solution 39
2 4 Two Paths to Follow 42
2 5 Changing the Grammar without Changing the Program 43
2 6 Using the Same Data for Several Programs 43
2 7 Exercises 46
2 8 Answers 46
3 Overview of Lisp 48
31A Guide to Lisp Style 49
3 2 Special Forms 50
Special Forms for Definitions 51
Special Forms for Conditionals 52
Special Forms for Dealing with Variables and Places 55
Functions and Special Forms for Repetition 57
Repetition through Recursion 62
Other Spedal Forms 64
Macros 66
Backquote Notation i 7
3 3 Functions on Lists 69
3 4 Equality and Internal Representation 70
3 5 Functions on Sequences 72
3 6 Functions for Maintaining Tables 73
3 7 Functions on Trees 76
3 8 Functions on Numbers 78
3 9 Functions on Sets 78
3 10 Destructive Functions 79
3 11 Overview of Data Types 81
3 12 Input/Output 83
3 13 Debugging Tools 85
3 14 Antibugging Tools 87
Timing Tools 90
3 15 Evaluation 91
3 16 Closures 92
3 17 Special Variables 93
3 18 Multiple Values 95
CONTENTS
XIX
3 19 More about Parameters 97
3 20 The Rest of Lisp 103
3 21 Exercises 103
3 22 Answers 103
PART II EARLY AI PROGRAMS 107
4 GPS: The General Problem Solver 109
4 1 Stage 1: Description 111
4 2 Stage 2: Specification 112
4 3 Stage 3: Implementation 113
4 4 Stage 4: Test 116
4 5 Stage 5: Analysis, or We Lied about the G 119
4 6 The Running Around the Block Problem 119
4 7 The Clobbered Sibling Goal Problem 119
4 8 The Leaping before You Look Problem 121
4 9 The Recursive Subgoal Problem 121
4 10 The Lack of Intermediate Information Problem 123
4 11 GPS Version 2: A More General Problem Solver 125
4 12 The New Domain Problem: Monkey and Bananas 132
4 13 The Maze Searching Domain 134
4 14 The Blocks World Domain 136
The Sussman Anomaly 142
4 15 Stage 5 Repeated: Analysis of Version 2 142
4 16 The Not Looking after You Don t Leap Problem 143
4 17 The Lack of Descriptive Power Problem 144
4 18 The Perfect Information Problem 145
4 19 The Interacting Goals Problem 145
4 20 The End of GPS 146
4 21 History and References 147
4 22 Exercises 148
4 23 Answers 149
5 Eliza: Dialog with a Machine 151
5 1 Describing and Specifying Eliza 154
5 2 Pattern Matching 154
5 3 Segment Pattern Matching 159
5 4 The Eliza Program: A Rule-Based Translator 163
5 5 History and References 167
XX
CONTENTS
5 6 Exercises 167
5 7 Answers 170
Building Software Tools 175
6 1 An Interactive Interpreter Tool 175
62A Pattern-Matching Tool 178
63A Rule-Based Translator Tool 188
64A Set of Searching Tools 189
Searching Trees 190
Guiding the Search 194
Search Paths 200
Guessing versus Guaranteeing a Good Solution 204
Searching Graphs 206
6 5 GPS as Search 211
6 6 History and References 213
6 7 Exercises 214
6 8 Answers 215
Student: Solving Algebra Word Problems 219
7 1 Translating English into Equations 220
7 2 Solving Algebraic Equations 225
7 3 Examples 231
7 4 History and References 234
7 5 Exercises 234
7 6 Answers 236
Symbolic Mathematics: A Simplification Program 238
8 1 Converting Infix to Prefix Notation 240
8 2 Simplification Rules 242
8 3 Associativity and Commutativity 246
8 4 Logs, Trig, and Differentiation 248
8 5 Limits of Rule-Based Approaches 251
8 6 Integration 252
8 7 History and References 259
8 8 Exercises 260
CONTENTS
xxi
PART 111 TOOLS AND TECHNIQUES 263
9 Efficiency Issues 265
9 1 Caching Results of Previous Computations: Memoization 269
9 2 Compiling One Language into Another 275
9 3 Delaying Computation 280
9 4 Indexing Data 288
9 5 Instrumentation: Deciding What to Optimize 288
96A Case Study in Efficiency: The SIMPLIFY Program 295
Memoization 296
Indexing 297
Compilation 298
The Single-Rule Compiler 300
The Rule-Set Compiler 303
9 7 History and References 307
9 8 Exercises 308
9 9 Answers 310
10 Low-Level Efficiency Issues 315
10 1 Use Declarations 316
10 2 Avoid Generic Functions 322
10 3 Avoid Complex Argument Lists 322
10 4 Avoid Unnecessary Consing 328
Avoid Consing: Unique Lists 334
Avoid Consing: Multiple Values 336
Avoid Consing: Resources 336
10 5 Use the Right Data Structures 339
The Right Data Structure: Variables 339
The Right Data Structure: Queues 341
The Right Data Structure: Tables 343
10 6 Exercises 346
10 7 Answers 347
11 Logic Programming 348
11 1 Idea 1: A Uniform Data Base 350
11 2 Idea 2: Unification of Logic Variables 352
Programming with Prolog 358
11 3 Idea 3: Automatic Backtracking 367
Approaches to Backtracking 372
XXII
CONTENTS
Anonymous Variables 372
11 4 The Zebra Puzzle 373
11 5 The Synergy of Backtracking and Unification 376
11 6 Destructive Unification 377
11 7 Prolog in Prolog 380
11 8 Prolog Compared to Lisp 380
11 9 History and References 382
11 10 Exercises 383
11 11 Answers 386
12 Compiling Logic Programs 388
12 1 A Prolog Compiler 390
12 2 Fixing the Errors in the Compiler 397
12 3 Improving the Compiler 399
12 4 Improving the Compilation of Unification 401
12 5 Further Improvements to Unification 407
12 6 The User Interface to the Compiler 408
12 7 Benchmarking the Compiler 411
12 8 Adding More Primitives 413
12 9 The Cut 420
12 10 Real Prolog 424
12 11 History and References 426
12 12 Exercises 426
12 13 Answers 429
13 Object-Oriented Programming 434
13 1 Object-Oriented Programming 435
13 2 Objects 436
13 3 Generic Functions 439
13 4 Classes 439
13 5 Delegation 441
13 6 Inheritance 443
13 7 CLOS: The Common Lisp Object System 445
13 8 A CLOS Example: Searching Tools 448
Best-First Search 451
13 9 Is CLOS Object-Oriented? 454
13 10 Advantages of Object-Oriented Programming 455
13 11 History and References 456
13 12 Exercises 459
CONTENTS
xxiii
14 Knowledge Representation and Reasoning 460
14 1 A Taxonomy of Representation Languages 462
14 2 Predicate Calculus and its Problems 463
14 3 A Logical Language: Prolog 465
14 4 Problems with Prolog s Expressiveness 465
14 5 Problems with Predicate Calculus s Expressiveness 468
14 6 Problems with Completeness 469
14 7 Problems with Efficiency: Indexing 472
14 8 A Solution to the Indexing Problem 472
14 9 A Solution to the Completeness Problem 482
14 10 Solutions to the Expressiveness Problems 485
Higher-Order Predications 485
Improvements 489
A Frame Language 493
Possible Worlds: Truth, Negation, and Disjunction 496
Unification, Equality, Types, and Skolem Constants 502
14 11 History and References 503
14 12 Exercises 504
14 13 Answers 506
PART IV ADVANCED AI PROGRAMS 507
15 Symbolic Mathematics with Canonical Forms 509
15 1 A Canonical Form for Polynomials 510
15 2 Differentiating Polynomials 518
15 3 Converting between Infix and Prefix 519
15 4 Benchmarking the Polynomial Simplifier 522
15 5 A Canonical Form for Rational Expressions 526
15 6 Extending Rational Expressions 527
15 7 History and References 528
15 8 Exercises 528
15 9 Answers 529
16 Expert Systems 530
16 1 Dealing with Uncertainty 532
16 2 Caching Derived Facts 536
16 3 Asking Questions 538
16 4 Contexts Instead of Variables 541
xxiv
CONTENTS
16 5 Backward-Chaining Revisited
16 6 Interacting with the Expert
16 7 Interacting with the Client
16 8 Mycin, A Medical Expert System
16 9 Alternatives to Certainty Factors
16 10 History and References
16 11 Exercises
16 12 Answers
17 Line-Diagram Labeling by Constraint Satisfaction
17 1 The Line-Labeling Problem 565
17 2 Combining Constraints and Searching 570
17 3 Labeling Diagrams 577
17 4 Checking Diagrams for Errors 586
17 5 History and References 594
17 6 Exercises 595
Search and the Game of Othello 596
18 1 The Rules of the Game 597
18 2 Representation Choices 599
18 3 Evaluating Positions 607
18 4 Searching Ahead: Minimax 610
18 5 Smarter Searching: Alpha-Beta Search 615
18 6 An Analysis of Some Games 617
18 7 The Tournament Version of Othello 622
18 8 Playing a Series of Games 626
18 9 More Efficient Searching 630
18 10 It Pays to Precycle 633
18 11 Killer Moves 634
18 12 Championship Programs: Iago and Bill 637
Mobility 637
Edge Stability 638
Combining the Factors 645
18 13 Other Techniques 646
Iterative Deepening 646
Forward Pruning 647
Nonspeculative Forward Pruning 647
Aspiration Search 648
Think-Ahead 649
543
548
550
552
557
558
559
562
CONTENTS
XXV
Hashing and Opening Book Moves 649
The End Game 649
Metareasoning 650
Learning 651
18 14 History and References 651
18 15 Exercises 652
18 16 Answers 653
19 Introduction to Natural Language 655
19 1 Parsing with a Phrase-Structure Grammar 656
19 2 Extending the Grammar and Recognizing Ambiguity 660
19 3 More Efficient Parsing 662
19 4 The Unknown-Word Problem 664
19 5 Parsing into a Semantic Representation 665
19 6 Parsing with Preferences 670
19 7 The Problem with Context-Free Phrase-Structure Rules 678
19 8 History and References 679
19 9 Exercises 679
19 10 Answers 680
20 Unification Grammars 684
20 1 Parsing as Deduction 685
20 2 Definite Clause Grammars 689
20 3 A Simple Grammar in DCG Format 692
20 4 A DCG Grammar with Quantifiers 696
20 5 Preserving Quantifier Scope Ambiguity 700
20 6 Long-Distance Dependencies 702
20 7 Augmenting DCG Rules 704
20 8 History and References 711
20 9 Exercises 712
20 10 Answers 713
21 A Grammar of English 715
21 1 Noun Phrases 717
21 2 Modifiers 718
21 3 Noun Modifiers 719
21 4 Determiners 721
21 5 Verb Phrases 722
21 6 Adverbs 723
XXVI
CONTENTS
21 7 Clauses 723
21 8 Sentences 725
21 9 XPs 727
21 10 Word Categories 730
21 11 The Lexicon 732
Verbs 734
Auxiliary Verbs 735
Nouns 736
Pronouns 736
Names 737
Adjectives 738
Adverbs 738
Articles 738
Cardinal and Ordinal Numbers 739
Prepositions 739
21 12 Supporting the Lexicon 739
21 13 Other Primitives 745
21 14 Examples 746
21 15 History and References 748
21 16 Exercises 749
PART V THE REST OF LISP 751
22 Scheme: An Uncommon Lisp 753
22 1 A Scheme Interpreter 756
22 2 Syntactic Extension with Macros 762
22 3 A Properly Tail-Recursive Interpreter 766
22 4 Throw, Catch, and Call/cc 768
22 5 An Interpreter Supporting Call/cc 773
22 6 History and References 776
22 7 Exercises 778
22 8 Answers 780
23 Compiling Lisp 784
23 1 A Properly Tail-Recursive Lisp Compiler 796
23 2 Introducing Call/cc 810
23 3 The Abstract Machine 810
23 4 A Peephole Optimizer 817
CONTENTS
xxvii
23 5 Languages with Different Lexical Conventions 821
23 6 History and References 825
23 7 Exercises 826
23 8 Answers 828
24 ANSI Common Lisp 834
24 1 Packages 834
The Seven Name Spaces 836
24 2 Conditions and Error Handling 837
Signaling Errors 838
Handling Errors 838
24 3 Pretty Printing 839
24 4 Series 839
24 5 The Loop Macro 840
Anatomy of a Loop 843
Iteration Control (26 6) 845
End-Test Control (26 7) 847
Value Accumulation (26 8) 848
Variable Initialization (26 9) 850
Conditional Execution (2610) 850
Unconditional Execution (2611) 852
Miscellaneous Features (2612) 852
24 6 Sequence Functions 852
Once-only: A Lesson in Macrology 853
Avoid Overusing Macros 855
MAP-INTO 857
REDUCE with :key 859
24 7 Exercises 863
24 8 Answers 863
25 Troubleshooting 866
25 1 Nothing Happens 867
25 2 Change to Variable Has No Effect 868
25 3 Change to Function Has No Effect 869
25 4 Values Change by Themselves 873
25 5 Built-In Functions Don t Find Elements 874
25 6 Multiple Values Are Lost 874
25 7 Declarations Are Ignored 875
xxviii
CONTENTS
25 8 My Lisp Does the Wrong Thing 876
25 9 How to Find the Function You Want 877
25 10 Syntax of LOOP 878
25 11 Syntax of COND 878
25 12 Syntax of CASE 879
25 13 Syntax of LET and LET* 880
25 14 Problems with Macros 880
25 15 A Style Guide to Lisp 887
When to Define a Function 887
When to Define a Special Variable 888
When to Bind a Lexical Variable 888
How to Choose a Name 888
Deriding on the Order of Parameters 889
25 16 Dealing with Files, Packages, and Systems 890
25 17 Portability Problems 894
25 18 Exercises 895
25 19 Answers 8%
Appendix: Obtaining the Code in this Book 897
Bibliography 901
Index
|
| any_adam_object | 1 |
| author | Norvig, Peter |
| author_facet | Norvig, Peter |
| author_role | aut |
| author_sort | Norvig, Peter |
| author_variant | p n pn |
| building | Verbundindex |
| bvnumber | BV006600529 |
| callnumber-first | Q - Science |
| callnumber-label | QA76 |
| callnumber-raw | QA76.6 |
| callnumber-search | QA76.6 |
| callnumber-sort | QA 276.6 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | ST 250 ST 300 |
| classification_tum | DAT 544f DAT 364f DAT 760f |
| ctrlnum | (OCoLC)24796537 (DE-599)BVBBV006600529 |
| dewey-full | 006.3 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3 |
| dewey-search | 006.3 |
| dewey-sort | 16.3 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Book |
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| id | DE-604.BV006600529 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T16:49:01Z |
| institution | BVB |
| isbn | 1558601910 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-004215415 |
| oclc_num | 24796537 |
| open_access_boolean | |
| owner | DE-739 DE-20 DE-29 DE-29T DE-19 DE-BY-UBM DE-210 DE-634 DE-11 |
| owner_facet | DE-739 DE-20 DE-29 DE-29T DE-19 DE-BY-UBM DE-210 DE-634 DE-11 |
| physical | XXVIII, 946 S. graph. Darst. |
| publishDate | 1992 |
| publishDateSearch | 1992 |
| publishDateSort | 1992 |
| publisher | Morgan Kaufmann Publ. |
| record_format | marc |
| spelling | Norvig, Peter Verfasser aut Paradigms of artificial intelligence programming case studies in common LISP Peter Norvig San Mateo, Calif. Morgan Kaufmann Publ. 1992 XXVIII, 946 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Literaturverz S. [901] - 918 Common Lisp (Langage de programmation) Inteligência artificial larpcal Intelligence artificielle Kunstmatige intelligentie gtt LISP gtt Programmation (Informatique) Künstliche Intelligenz Artificial intelligence COMMON LISP (Computer program language) Computer programming Common-LISP (DE-588)4191732-7 gnd rswk-swf Programmierung (DE-588)4076370-5 gnd rswk-swf LISP (DE-588)4035918-9 gnd rswk-swf Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Common-LISP (DE-588)4191732-7 s DE-604 Künstliche Intelligenz (DE-588)4033447-8 s Programmierung (DE-588)4076370-5 s LISP (DE-588)4035918-9 s 1\p DE-604 HEBIS Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=004215415&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Norvig, Peter Paradigms of artificial intelligence programming case studies in common LISP Common Lisp (Langage de programmation) Inteligência artificial larpcal Intelligence artificielle Kunstmatige intelligentie gtt LISP gtt Programmation (Informatique) Künstliche Intelligenz Artificial intelligence COMMON LISP (Computer program language) Computer programming Common-LISP (DE-588)4191732-7 gnd Programmierung (DE-588)4076370-5 gnd LISP (DE-588)4035918-9 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd |
| subject_GND | (DE-588)4191732-7 (DE-588)4076370-5 (DE-588)4035918-9 (DE-588)4033447-8 |
| title | Paradigms of artificial intelligence programming case studies in common LISP |
| title_auth | Paradigms of artificial intelligence programming case studies in common LISP |
| title_exact_search | Paradigms of artificial intelligence programming case studies in common LISP |
| title_full | Paradigms of artificial intelligence programming case studies in common LISP Peter Norvig |
| title_fullStr | Paradigms of artificial intelligence programming case studies in common LISP Peter Norvig |
| title_full_unstemmed | Paradigms of artificial intelligence programming case studies in common LISP Peter Norvig |
| title_short | Paradigms of artificial intelligence programming |
| title_sort | paradigms of artificial intelligence programming case studies in common lisp |
| title_sub | case studies in common LISP |
| topic | Common Lisp (Langage de programmation) Inteligência artificial larpcal Intelligence artificielle Kunstmatige intelligentie gtt LISP gtt Programmation (Informatique) Künstliche Intelligenz Artificial intelligence COMMON LISP (Computer program language) Computer programming Common-LISP (DE-588)4191732-7 gnd Programmierung (DE-588)4076370-5 gnd LISP (DE-588)4035918-9 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd |
| topic_facet | Common Lisp (Langage de programmation) Inteligência artificial Intelligence artificielle Kunstmatige intelligentie LISP Programmation (Informatique) Künstliche Intelligenz Artificial intelligence COMMON LISP (Computer program language) Computer programming Common-LISP Programmierung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=004215415&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT norvigpeter paradigmsofartificialintelligenceprogrammingcasestudiesincommonlisp |