Artificial Intelligence: Foundations of Computational Agents – David Poole, Alan K. Mackworth – 1st Edition

Description

The past few decades have witnessed the emergence of artificial intelligence as a serious scientific and engineering discipline. Artificial Intelligence: Fundamentals of Computational Agents is a textbook aimed at first- to senior-year undergraduates and graduate students. Introduces 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 big picture general.

The book balances theory and experiment, shows how to link them intimately, and develops the science of AI along with its engineering applications. Although structured like a textbook, the book’s simple, self-contained style will also appeal to a wide audience of independent professionals, researchers, and students. AI is a rapidly developing field: this book summarizes the latest results without being exhaustive or encyclopedic. It teaches the principles and tools that will allow readers to explore and learn on their own. The text is supported by an online learning environment, artint.info, for students to experiment with major AI algorithms, plus problems, animations, lecture slides, and a knowledge representation system for experimentation and analysis. Problem resolution.

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  • Preface
    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

    II Representing and Reasoning
    3 States and Searching
    4 Features and Constraints
    5 Propositions and Inference
    6 Reasoning Under Uncertainty

    III Learning and Planning
    7 Learning: Overview and Supervised Learning8 Planning with Certainty
    8 Planning with Certainty
    9 Planning Under Uncertainty
    10 Multiagent Systems
    11 Beyond Supervised Learning

    IV Reasoning About Individuals and Relations
    12 Individuals and Relations
    13 Ontologies and Knowledge-Based Systems
    14 Relational Planning, Learning, and Probabilistic Reasoning

    V The Big Picture
    15 Retrospect and Prospect
    A Mathematical Preliminaries and Notation
    Bibliography
    Index
  • Citation

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