| Description |
1 online resource (977 pages) |
| Contents |
Cover; Half Title; Title Page; Copyright Page; Table of Contents; Preface; Part I: Lisp Programming; 1. Lisp Review; 1.1 Data Structures; 1.2 Program Structures; 1.3 Primitive Operations on S-expressions; 1.4 Tree Structures; 1.5 Lists; 1.6 Mapping Functions; 1.7 LAMBDA Expressions; 1.8 Atoms; 1.9 Inside Lisp; 1.10 Equality; 1.11 Local versus free variables; 1.12 Lisp style; 1.13 Keywords; 1.14 More lambda-list keywords; 2. Macros and Read-Macros; 2.1 Read-Macros; 2.2 The Backquote Read-Macro; 2.3 Terminating Read-Macros; 2.4 Macros; 2.5 Generating new symbols |
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2.6 BIND: A Macro For Special Variables3. Data Structures and Control Structures in Lisp; 3.1 The Need for Data Types; 3.2 The Conservative Approach to Type Definition; 3.3 The Liberal Approach; 3.4 The Radical Approach; 3.5 Control Structures; 3.6 Basic control structure; 3.7 Local functions: FLET and LABELS; 3.8 Interrupting the normal flow; 3.9 Redirecting the flow of control: GO; 3.10 ITERATE; 3.11 DO; 3.12 Iteration and lists: the mapping functions; 3.13 Defining the FOR-macro; 3.14 CATCH and THROW; 3.15 UNWIND-PROTECT; 3.16 BIND; 3.17 Conclusion; 4. Input/Output in Lisp; 4.1 Streams |
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4.2 READ-CHAR, READ-LINE, and READ4.3 PRIN1, PRINC and TERPRI; 4.4 PRINT, PPRINT, and FORMAT; 4.5 The MSG Macro; 4.6 Separating I/O from Your Functions; 5. Compiling Your Program and Your Program's Program; 5.1 What Is Compilation?; 5.2 Implications for Al Programs; 5.3 Example: Regular Expressions; 5.4 What the Lisp Compiler Does; 5.5 Compiler Declarations; 5.6 Macros in Compiled Code; 5.7 Variables in Compiled Code; 5.8 Lexical Scoping Versus EVAL and SET; 5.9 Ignored Variables; 6. Data-Driven Programming and Other Programming Techniques; 6.1 Data-driven Programming |
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6.2 Association Lists, Property Lists, and Hash Tables6.3 Reimplementing MSG; 6.4 Data-Driven Programming as an Organizational Device; 6.5 Set Operations on Lists; 6.6 Headed Lists and Queues; 7. Higher-Order Functions, Continuations, and Coroutines; 7.1 Passing Procedures In and Out; 7.2 Continuations and Tail-Recursion; 7.3 Continuations and Multiple Values; 7.4 Coroutines; 7.5 Continuations and Control Flow: CALL-WITH-CURRENT-CONTINUATION; 7.6 Problems with Continuation Passing; Part II: Al Programming Techniques; 8. Simple Discrimination Nets; 8.1 The General Discrimination Net |
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8.2 Database Discrimination Nets-Lists of Atoms8.3 Database Discrimination Nets-General S-expressions; 8.4 Implementing Discrimination Trees with Continuations; 9. Agenda Control Structures; 9.1 Introduction; 9.2 Best-First Tree Search; 9.3 Coroutines and Agendas; 9.4 Design Alternatives for Agendas; 9.5 Generated Lists; 10. Deductive Information Retrieval; 10.1 Introduction; 10.2 Database-defined Predicates; 10.3 Connectives, Variables, and Inference Rules; 10.4 Existential Quantification; 10.5 Coming to Terms; 10.6 Issues; 10.7 Deductive Retrieval; 10.8 A Unification Algorithm |
| Summary |
Artificial intelligence research has thrived in the years since this best-selling AI classic was first published. The revision encompasses these advances by adapting its coding to Common Lisp, the well-documented language standard, and by bringing together even more useful programming tools. Today's programmers in AI will find this volume's superior coverage of programming techniques and easily applicable style anything but common |
| Notes |
10.9 A Deductive Retriever |
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Print version record |
| Subject |
Artificial intelligence -- Data processing.
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Computer programming.
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LISP (Computer program language)
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computer programming.
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COMPUTERS -- General.
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Artificial intelligence -- Data processing
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Computer programming
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LISP (Computer program language)
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| Form |
Electronic book
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| Author |
Riesbeck, Christopher K
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McDermott, Drew V
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Meehan, James R
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| ISBN |
9781317767985 |
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1317767985 |
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