An Introduction to Artificial Intelligence

ISBN-13: 9781138435841 / Angielski / Twarda / 2017

Janet Finlay

Opis

Offers an accessible and comprehensive introduction to artificial intelligence. Featuring extensive worked examples and exercises, the text is suitable for modular undergraduate degrees or MSc conversion courses.

Spis treści

Preface -- Introduction -- What is artificial intelligence? History of artificial intelligence The future for AI -- 1 Knowledge in AI -- 1.1 Overview -- 1.2 Introduction -- 1.3 Representing knowledge -- 1.4 Metrics for assessing knowledge representation schemes -- 1.5 Logic representations -- 1.6 Procedural representation -- 1.7 Network representations -- 1.8 Structured representations -- 1.9 General knowledge -- 1.10 The frame problem -- 1.11 Knowledge elicitation -- 1.12 Summary -- 1.13 Exercises -- 1.14 Recommended further reading -- 2 Reasoning -- 2.1 Overview -- 2.2 What is reasoning? -- 2.3 Forward and backward reasoning -- 2.4 Reasoning with uncertainty -- 2.5 Summary -- 2.6 Exercises -- 2.7 Recommended further reading -- 3 Search -- 3.1 Introduction -- 3.2 Exhaustive search and simple pruning -- 3.3 Heuristic search -- 3.4 Knowledge-rich search -- 3.5 Summary -- 3.6 Exercises -- 3.7 Recommended further reading -- 4 Machine learning -- 4.1 Overview -- 4.2 Why do we want machine learning? -- 4.3 How machines learn -- 4.4 Deductive learning -- 4.5 Inductive learning -- 4.6 Explanation-based learning -- 4.7 Example: Query-by-Browsing -- 4.8 Summary -- 4.9 Recommended further reading -- 5 Game playing -- 5.1 Overview -- 5.2 Introduction -- 5.3 Characteristics of game playing -- 5.4 Standard games -- 5.5 Non-zero-sum games and simultaneous play -- 5.6 The adversary is life! -- 5.7 Probability -- 5.8 Summary -- 5.9 Exercises -- 5.10 Recommended further reading -- 6 Expert systems -- 6.1 Overview -- 6.2 What are expert systems? -- 6.3 Uses of expert systems -- 6.4 Architecture of an expert system -- 6.5 Examples of four expert systems -- 6.6 Building an expert system -- 6.7 Limitations of expert systems -- 6.8 Hybrid expert systems -- 6.9 Summary -- 6.10 Exercises -- 6.11 Recommended further reading -- 7 Natural language understanding -- 7.1 Overview -- 7.2 What is natural language understanding? -- 7.3 Why do we need natural language understanding? -- 7.4 Why is natural language understanding difficult? -- 7.5 An early attempt at natural language understanding: SHRDLU -- 7.6 How does natural language understanding work? -- 7.7 Syntactic analysis -- 7.8 Semantic analysis -- 7.9 Pragmatic analysis -- 7.10 Summary -- 7.11 Exercises -- 7.12 Recommended further reading -- 7.13 Solution to SHRDLU problem -- 8 Computer vision -- 8.1 Overview -- 8.2 Introduction -- 8.3 Digitization and signal processing -- 8.4 Edge detection -- 8.5 Region detection -- 8.6 Reconstructing objects -- 8.7 Identifying objects -- 8.8 Multiple images -- 8.9 Summary -- 8.10 Exercises -- 8.11 Recommended further reading -- 9 Planning and robotics -- 9.1 Overview -- 9.2 Introduction -- 9.3 Global planning -- 9.4 Local planning -- 9.5 Limbs, legs and eyes -- 9.6 Practical robotics -- 9.7 Summary -- 9.8 Exercises -- 9.9 Recommended further reading -- 10 Agents -- 10.1 Overview -- 10.2 Software agents -- 10.3 Co-operating agents and distributed AI -- 10.4 Summary -- 10.5 Exercises -- 10.6 Recommended further reading -- 11 Models of the mind -- 11.1 Overview -- 11.2 Introduction -- 11.3 What is the human mind? -- 11.4 Production system models -- 11.5 Connectionist models of cognition -- 11.6 Summary -- 11.7 Exercises -- 11.8 Recommended further reading -- 11.9 Notes -- 12 Epilogue: philosophical and sociological issues -- 12.1 Overview -- 12.2 Intelligent machines or engineering tools? -- 12.3 What is intelligence? -- 12.4 Computational argument vs. Searle's Chinese Room -- 12.5 Who is responsible? -- 12.6 Morals and emotions -- 12.7 Social implications -- 12.8 Summary -- 12.9 Recommended further reading -- Bibliography -- Index.

O autorze

Janet Finlay