Artificial Intelligence

David Poole is a Professor of Computer Science at the University of British Columbia. He is known for his research on abductive and default reasoning, probabilistic inference, and relational probabilistic models, and he has recently been working on semantic science, combining ontologies, data, and rich probabilistic theories. He is a co-author of Computational Intelligence: A Logical Approach (1998), co-chair of AAAI-10 (Twenty-Fourth AAAI Conference on Artificial Intelligence), and co-editor of the Proceedings of the Tenth Conference in Uncertainty in Artificial Intelligence (1994). Poole is the former associate editor and on the advisory board of the Journal of AI Research. He is an associate editor of AI Journal and on the editorial boards of AI Magazine and AAAI Press. He is the secretary of the Association for Uncertainty in Artificial Intelligence and is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI). Alan Mackworth is a Professor of Computer Science and Canada Research Chair in Artificial Intelligence at the University of British Columbia. He is known for his research on constraint-based systems and agents, hybrid systems, and robot soccer. He is a co-author of Computational Intelligence: A Logical Approach. He was President and Trustee of International Joint Conferences on AI (IJCAI) Inc. Mackworth was Vice President and President of the Canadian Society for Computational Studies of Intelligence (CSCSI). He has served as President of the Association for the Advancement of Artificial Intelligence (AAAI). He also served as the founding Director of the UBC Laboratory for Computational Intelligence. He is a Fellow of AAAI, the Canadian Institute for Advanced Research, and the Royal Society of Canada.

Part I. Agents in the World: What Are Agents and How Can They Be Built?: 1. Artificial intelligence and agents; 2. Agent architectures and hierarchical control; Part II. Representing and Reasoning: 3. States and searching; 4. Features and constraints; 5. Propositions and inference; 6. Reasoning under uncertainty; Part III. Learning and Planning: 7. Learning: overview and supervised learning; 8. Planning with certainty; 9. Planning under uncertainty; 10. Multiagent systems; 11. Beyond supervised learning; Part IV. Reasoning about Individuals and Relations: 12. Individuals and relations; 13. Ontologies and knowledge-based systems; 14. Relational planning, learning and probabilistic reasoning; Part V. The Big Picture: 15. Retrospect and prospect; Appendix A. Mathematical preliminaries and notation.