Paradigms of artificial intelligence programming case studies in Common Lisp
Paradigms of AI Programming is the first text to teach advanced Common Lisp techniques in the context of building major AI systems. By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical...
| Otros Autores: | , , , , , , , |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
San Francisco, California :
Morgan Kaufmann Publishers
1992.
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| Edición: | First edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009629638306719 |
Tabla de Contenidos:
- Front Cover; Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp; Copyright Page; Preface; Table of Contents; PART I: INTRODUCTION TO COMMON LISP; CHAPTER 1. Introduction to Lisp; 1.1 Symbolic Computation; 1.2 Variables; 1.3 Special Forms; 1.4 Lists; 1.5 Defining New Functions; 1.6 Using Functions; 1.7 Higher-Order Functions; 1.8 Other Data Types; 1.9 Summary: The Lisp Evaluation Rule; 1.10 What Makes Lisp Different?; 1.11 Exercises; 1.12 Answers; CHAPTER 2. A Simple Lisp Program; 2.1 A Grammar for a Subset of English; 1.1 A Straightforward Solution
- 2.3 A Rule-Based Solution2.4 Two Paths to Follow; 2.5 Changing the Grammar without Changingthe Program; 2.6 Using the Same Data for Several Programs; 2.7 Exercises; 2.8 Answers; CHAPTER 3. Overview of Lisp; 3.1 A Guide to Lisp Style; 3.2 Special Forms; 3·3 Functions on Lists; 3.4 Equality and Internal Representation; 3.5 Functions on Sequences; 3.6 Functions for Maintaining Tables; 3.7 Functions on Trees; 3.8 Functions on Numbers; 3.9 Functions on Sets; 3.10 Destructive Functions; 3.11 Overview of Data Types; 3.12 Input/Output; 3.12 Input/Output; 3.13 Debugging Tools; 3.14 Antibugging Tools
- 3.15 Evaluation3.16 Closures; 3.17 Special Variables; 3.18 Multiple Values; 3.19 More about Parameters; 3.20 The Rest of Lisp; 3.21 Exercises; 3.22 Answers; PART II: EARLY AI PROGRAMS; CHAPTER 4. GPS: The GeneraProblem Solver; 4.1 Stage 1: Description; 4.2 Stage 2: Specification; 4.3 Stage 3: Implementation; 4.4 Stage 4: Test; 4.5 Stage 5: Analysis, or ''We Lied about the C; 4.6 The Running Around the Block Problem; 4.7 The Clobbered Sibling Goal Problem; 4 · 8 The Leaping before You Look Problem; 4.9 The Recursive Subgoal Problem; 4.10 The Lack of Intermediate InformationProblem
- 4.11 GPS Version 2: A More GeneralProblem Solver4.12 The New Domain Problem: Monkeyand Bananas; 4.13 The Maze Searching Domain; 4·14 The Blocks World Domain; 4.15 Stage 5 Repeated: Analysis of Version 2; 4.16 The Not Looking after You Don^tLeap Problem; 4.17 The Lack of Descriptive Power Problem; 4.18 The Perfect Information Problem; 4.19 The Interacting Goals Problem; 4.20 The End of GPS; 4.21 History and References; 4.22 Exercises; 4.23 Answers; CHAPTER 5. ELIZA: Dialog with a Machine; 5.1 Describing and Specifying ELIZA; 5.3 Segment Pattern Matching
- 5.4 The ELIZA Program: A Rule-BasedTranslator5.5 History and References; 5.6 Exercises; 5.7 Answers; CHAPTER 6. Building Software Tools; 6.1 An Interactive Interpreter Tool; 6.2 A Pattern-Matching Tool; 6.3 A Rule-Based Translator Tool; 6.4 A Set of Searching Tools; 6.5 GPS as Search; 6.6 History and References; 6.7 Exercises; 6.8 Answers; CHAPTER 7. STUDENT: Solving AlgebraWord Problems; 7.1 Translating English into Equations; 7.2 Solving Algebraic Equations; 7.3 Examples; 7.4 History and References; 7.5 Exercises; 7.6 Answers; CHAPTER 8. Symbolic Mathematics:A Simplification Program
- 8.1 Converting Infix to Prefix Notation
