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| Artificial Intelligence: Its Roots and Scope | |
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| AI: History and Applications | |
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| From Eden to ENIAC: Attitudes toward Intelligence, Knowledge, and Human Artifice | |
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| Overview of AI Application Areas | |
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| Artificial Intelligence A Summary | |
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| Epilogue and References | |
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| Exercises | |
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| Artificial Intelligence as Representation and Search | |
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| The Predicate Calculus | |
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| Introduction | |
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| The Propositional Calculus | |
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| The Predicate Calculus | |
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| Using Inference Rules to Produce Predicate Calculus Expressions | |
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| Application: A Logic-Based Financial Advisor | |
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| Epilogue and References | |
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| Exercises | |
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| Structures and Strategies for State Space Search | |
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| Introduction | |
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| Graph Theory | |
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| Strategies for State Space Search | |
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| Using the State Space to Represent Reasoning with the Predicate Calculus | |
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| Epilogue and References | |
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| Exercises | |
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| Heuristic Search | |
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| Introduction | |
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| Hill Climbing and Dynamic Programming | |
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| The Best-First Search Algorithm | |
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| Admissibility, Monotonicity, and Informedness | |
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| Using Heuristics in Games | |
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| Complexity Issues | |
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| Epilogue and References | |
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| Exercises | |
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| stochastic methods | |
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| Introduction | |
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| The Elements of Counting | |
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| Elements of Probability Theory | |
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| Applications of the Stochastic Methodology | |
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| Bayes Theorem | |
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| Epilogue and References | |
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| Exercises | |
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| Control and Implementation of State Space Search | |
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| Introduction | |
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| Recursion-Based Search | |
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| Production Systems | |
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| The Blackboard Architecture for Problem Solving | |
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| Epilogue and References | |
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| Exercises | |
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| Capturing Intelligence: The AI Challenge | |
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| Knowledge Representation | |
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| Issues in Knowledge Representation | |
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| A Brief History of AI Representational Systems | |
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| Conceptual Graphs: A Network Language | |
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| Alternative Representations and Ontologies | |
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| Agent Based and Distributed Problem Solving | |
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| Epilogue and References | |
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| Exercises | |
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| Strong Method Problem Solving | |
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| Introduction | |
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| Overview of Expert System Technology | |
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| Rule-Based Expert Systems | |
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| Model-Based, Case Based, and Hybrid Systems | |
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| Planning | |
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| Epilogue and References | |
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| Exercises | |
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| Reasoning in Uncertain Situations | |
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| Introduction | |
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| Logic-Based Abductive Inference | |
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| Abduction: Alternatives to Logic | |
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| The Stochastic Approach to Uncertainty | |
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| Epilogue and References | |
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| Exercises | |
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| Machine Learning | |
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| Machine Learning: Symbol-Based | |
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| Introduction | |
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| A Framework for Symbol-based Learning | |
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| Version Space Search | |
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| The ID3 Decision Tree Induction Algorithm | |
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| Inductive Bias and Learnability | |
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| Knowledge and Learning | |
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| Unsupervised Learning | |
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| Reinforcement Learning | |
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| Epilogue and References | |
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| Exercises | |
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| Machine Learning: Connectionist | |
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| Introduction | |
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| Foundations for Connectionist Networks | |
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| Perceptron Learning | |
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| Backpropagation Learning | |
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| Competitive Learning | |
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| Hebbian Coincidence Learning | |
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| Attractor Networks or Memories | |
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| Epilogue and References | |
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| Exercises 506 | |