Artificial Intelligence: Foundations of Computational Agents, 3rd Edition

✍ Scribed by David L. Poole. Alan K. Mackworth

• Publisher: Cambridge University Press
• Year: 2024
• Tongue: English
• Leaves: 903
• Edition: 3
• Category: Library

✦ Synopsis

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. An invaluable teaching package for undergraduate and graduate AI courses, this comprehensive textbook is accompanied by lecture slides, solutions, and code.

✦ Table of Contents

02.0_pp_ii_iv_Reviews
04.0_pp_vi_vi_Copyright_page
05.0_pp_vii_viii_Dedication
06.0_pp_ix_xx_Contents
07.0_pp_xxi_xxvi_Preface
08.0_pp_1_76_Agents_in_the_World
08.1_pp_3_50_Artificial_Intelligence_and_Agents
08.2_pp_51_76_Agent_Architectures_and_Hierarchical_Control
09.0_pp_77_258_Reasoning_and_Planning_with_Certainty
09.1_pp_79_126_Searching_for_Solutions
09.2_pp_127_176_Reasoning_with_Constraints
09.3_pp_177_230_Propositions_and_Inference
09.4_pp_231_258_Deterministic_Planning
10.0_pp_259_514_Learning_and_Reasoning_with_Uncertainty
10.1_pp_261_326_Supervised_Machine_Learning
10.2_pp_327_374_Neural_Networks_and_Deep_Learning
10.3_pp_375_458_Reasoning_with_Uncertainty
10.4_pp_459_490_Learning_with_Uncertainty
10.5_pp_491_514_Causality
11.0_pp_515_642_Planning_and_Acting_with_Uncertainty
11.1_pp_517_582_Planning_with_Uncertainty
11.2_pp_583_608_Reinforcement_Learning
11.3_pp_609_642_Multiagent_Systems
12.0_pp_643_764_Representing_Individuals_and_Relations
12.1_pp_645_700_Individuals_and_Relations
12.2_pp_701_730_Knowledge_Graphs_and_Ontologies
12.3_pp_731_764_Relational_Learning_and_Probabilistic_Reasoning
13.0_pp_765_796_The_Big_Picture
13.1_pp_767_784_The_Social_Impact_of_Artificial_Intelligence
13.2_pp_785_796_Retrospect_and_Prospect
14.1_pp_797_802_Mathematical_Preliminaries_and_Notation
14.2_pp_803_806_Mapping_to_Open-Source_Packages
15.0_pp_807_842_References
16.0_pp_843_846_Index_of_Algorithms
17.0_pp_847_870_Index