Artificial Intelligence: Foundations of Computational Agents 2/e [Poole] 9781107195394

Fully revised and updated, this third edition includes three new chapters on neural networks and deep learning including generative AI, causality, and the social, ethical and regulatory impacts of artificial intelligence. All parts have been updated with the methods that have been proven to work. The book's novel agent design space provides a coherent framework for learning, reasoning and decision making. Numerous realistic applications and examples facilitate student understanding. Every concept or algorithm is presented in pseudocode and open source AIPython code, enabling students to experiment with and build on the implementations. Five larger case studies are developed throughout the book and connect the design approaches to the applications. Each chapter now has a social impact section, enabling students to understand the impact of the various techniques as they learn them. 

頁數：824
版次：第2版
年份：2017年
規格：精裝/單色
ISBN：9781107195394

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. Reasoning, Planning and Learning with Certainty:
3. Searching for solutions
4. Reasoning with constraints
5. Propositions and inference
6. Planning with certainty
7. Supervised machine learning
Part III. Reasoning, Learning and Acting with Uncertainty:
8. Reasoning with uncertainty
9. Planning with uncertainty
10. Learning with uncertainty
11. Multiagent systems
12. Learning to act
Part IV. Reasoning, Learning and Acting with Individuals and Relations:
13. Individuals and relations
14. Ontologies and knowledge-based systems
15. Relational planning, learning, and probabilistic reasoning
Part V. Retrospect and Prospect:
16. Retrospect and prospect
Appendix A. Mathematical preliminaries and notation.