Poole David L., Mackworth Alan K. Artificial Intelligence. Foundations of Computational Agents

Cambridge University Press, 2010. — 682 p. — ISBN: 9780521519007.Recent decades have witnessed the emergence of artificial intelligence as a serious science and engineering discipline. This textbook, aimed at junior to senior undergraduate students and first-year graduate students, presents artificial intelligence (AI) using a coherent framework to study the design of intelligent computational agents. By showing how basic approaches fit into a multidimensional design space, readers can learn the fundamentals without losing sight of the bigger picture. The book balances theory and experiment, showing how to link them intimately together, and develops the science of AI together with its engineering applications. Although structured as a textbook, the book's straightforward, self-contained style will also appeal to a wide audience of professionals, researchers, and independent learners. AI is a rapidly developing field: this book encapsulates the latest results without being exhaustive and encyclopedic. The text is supported by an online learning environment, AIspace, http://aispace.org, so that students can experiment with the main AI algorithms plus problems, animations, lecture slides, and a knowledge representation system, AIlog, for experimentation and problem solving.
Presents a coherent development of AI theory in terms of design space for building an intelligent agent
Offers practical descriptions of algorithms, linked to theory;
Offers animations of the main algorithms in AIspace (http://aispace.org);
Provides various routes through the material to allow for a variety of different one-term or two-term courses.Agents in the World: What Are Agents and How Can They Be Built?
Artificial Intelligence and Agents
Agent Architectures and Hierarchical Control
Representing and Reasoning
States and Searching
Features and Constraints
Propositions and Inference
Reasoning Under Uncertainty
Learning and Planning
Learning: Overview and Supervised Learning
Planning with Certainty
Planning Under Uncertainty
Multiagent Systems
Beyond Supervised Learning
Reasoning About Individuals and Relations
Individuals and Relations
Ontologies and Knowledge-Based Systems
Relational Planning, Learning, and Probabilistic Reasoning
The Big Picture
Retrospect and Prospect
Appendix: Mathematical Preliminaries and Notation

Index