Artificial Intelligence: Foundations of Computational Agents

Artificial intelligence, including machine learning, has emerged as a transformational science and engineering discipline. Artificial Intelligence: Foundations of Computational Agents presents AI using a coherent framework to study the design of intelligent computational agents. By showing how the basic approaches fit into a multidimensional design space, readers learn the fundamentals without losing sight of the bigger picture. The new edition also features expanded coverage on machine learning material, as well as on the social and ethical consequences of AI and ML. The book balances theory and experiment, showing how to link them together, and develops the science of AI together with its engineering applications. Although structured as an undergraduate and graduate textbook, the book's straightforward, self-contained style will also appeal to an audience of professionals, researchers, and independent learners. The second edition is well-supported by strong pedagogical features and online resources to enhance student comprehension.

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• Artificial Intelligence: A Modern Approach
• Artificial Intelligence: A Modern Approach (3rd Edition)
• Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series)
• Machine Learning: An Applied Mathematics Introduction
• Quantum Computing for Everyone (The MIT Press)
• A Programmer's Introduction to Mathematics
• Introduction to Deep Learning (The MIT Press)
• Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
• Neural Networks and Deep Learning: A Textbook