Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgements
- 1 Introduction
- 2 Search Spaces
- 3 Blind Search
- 4 Heuristic Search
- 5 Stochastic Local Search
- 6 Algorithm A* and Variations
- 7 Problem Decomposition
- 8 Chess and Other Games
- 9 Automated Planning
- 10 Deduction as Search
- 11 Search in Machine Learning
- 12 Constraint Satisfaction
- Appendix: Algorithm and Pseudocode Conventions
- References
- Index
Preface
Published online by Cambridge University Press: 30 April 2024
- Frontmatter
- Contents
- Preface
- Acknowledgements
- 1 Introduction
- 2 Search Spaces
- 3 Blind Search
- 4 Heuristic Search
- 5 Stochastic Local Search
- 6 Algorithm A* and Variations
- 7 Problem Decomposition
- 8 Chess and Other Games
- 9 Automated Planning
- 10 Deduction as Search
- 11 Search in Machine Learning
- 12 Constraint Satisfaction
- Appendix: Algorithm and Pseudocode Conventions
- References
- Index
Summary
This book is meant for the serious practitioner-to-be of constructing intelligent machines. Machines that are aware of the world around them, that have goals to achieve, and the ability to imagine the future and make appropriate choices to achieve those goals. It is an introduction to a fundamental building block of artificial intelligence (AI). As the book shows, search is central to intelligence.
Clearly AI is not one monolithic algorithm but a collection of processes working in tandem, an idea espoused by Marvin Minsky in his book The Society of Mind (1986). Human problem solving has three critical components. The ability to make use of experiences stored in memory; the ability to reason and make inferences from what one knows; and the ability to search through the space of possibilities. This book focuses on the last of these. In the real world we sense the world using vision, sound, touch, and smell. An autonomous agent will need to be able to do so as well. Language, and the written word, is perhaps a distinguishing feature of the human species. It is the key to communication which means that human knowledge becomes pervasive and is shared with future generations. The development of mathematical sciences has sharpened our understanding of the world and allows us to compute probabilities over choices to take calculated risks. All these abilities and more are needed by an autonomous agent.
Can one massive neural network be the embodiment of AI? Certainly, the human brain as a seat of intelligence suggests that. Everything we humans do has its origin in activity in our brains, which we call the mind. Perched on the banks of a stream in the mountains we perceive the world around us and derive a sense of joy and well-being. In a fit of contented creativity, we may pen an essay or a poem using our faculty of language. We may call a friend on the phone and describe the scene around us, allowing the friend to visualize the serene surroundings. She may reflect upon her own experiences and recall a holiday she had on the beach. You might start humming your favourite song and then be suddenly jolted out of your reverie remembering that friends are coming over for dinner. You get up and head towards your home with cooking plans brewing in your head.
- Type
- Chapter
- Information
- Search Methods in Artificial Intelligence , pp. xi - xiiPublisher: Cambridge University PressPrint publication year: 2024