Table of Contents
1.2 Approaches to Artificial Intelligence
1.5 Additional Readings and Discussion
Introduction to Reactive Machines
2.2 Representing and Implementing Action Functions
2.3 Additional Readings and Discussion
3.4 Generalization, Accuracy, and Overfitting
3.5 Additional Readings and Discussion
4.3 Additional Readings and Discussion
5.1 Representing the Environment by Feature Vectors
5.5 Additional Readings and Discussion
6.3 Two Stages of Robot Vision
6.6 Stereo Vision and Depth Information
6.7 Additional Readings and Discussion
Introduction to Search in State Spaces
7.3 Searching Explicit State Spaces
7.4 Feature-Based State Spaces
7.6 Additional Readings and Discussion
8.1 Formulating the State Space
8.2 Components of Implicit State-Space Graphs
8.4 Depth-First or Backtracking Search
8.6 Additional Readings and Discussion
9.1 Using Evaluation Functions
9.2 A General Graph-Searching Algorithm
9.3 Heuristic Functions and Search Efficiency
9.4 Additional Readings and Discussion
10. Planning, Acting, and Learning
10.3 Learning Heuristic Functions
10.5 Additional Readings and Discussion
11. Alternative Search Formulations and Applications
12.4 The Search Efficiency of the Alpha-Beta Procedure
12.7 Learning Evaluation Functions
12.8 Additional Readings and Discussion
III: Knowledge Representation and Reasoning
Introduction to Knowledge Representation and Reasoning
13. The Propositional Calculus
13.1 Using Constraints on Feature Values
13.6 Soundness and Completeness
14. Resolution in the Propositional Calculus
14.1 A New Rule of Inference: Resolution
14.2 Converting Arbitrary wffs to Conjunctions of Clauses
14.4 Resolution Refutation Search Strategies
15.2 The Language and Its Syntax
15.6 Predicate Calculus as a Language for Representing Knowledge
15.7 Additional Readings and Discussion
16. Resolution in the Predicate Calculus
16.2 Predicate-Calculus Resolution
16.3 Completeness and Soundness
16.4 Converting Arbitrary wffs to Clause Form
16.5 Using Resolution to Prove Theorems
16.8 Additional Readings and Discussion
17.1 Confronting the Real World
17.2 Reasoning Using Horn Clauses
17.3 Maintenance in Dynamic Knowledge Bases
17.4 Rule-Based Expert Systems
17.6 Additional Readings and Discussion
18. Representing Commonsense Knowledge
18.3 Knowledge Representation by Networks
18.4 Additional Readings and Discussion
19. Reasoning with Uncertain Information
19.1 Review of Probability Theory
19.4 Patterns of Inference in Bayes Networks
19.7 Probabilistic Inference in Polytrees
19.8 Additional Readings and Discussion
20. Learning and Acting with Bayes Nets
20.2 Probabilistic Inference and Action
20.3 Additional Readings and Discussion
IV: Planning Methods Based on Logic
Introduction to Planning Methods Based on Logic
21.1 Reasoning about States and Actions
21.4 Additional Readings and Discussion
22.2 Plan Spaces and Partial-Order Planning
22.5 Additional Readings and Discussion
V: Communication and Integration
Introduction to Communication and Integration
23.3 A Modal Logic of Knowledge
23.4 Additional Readings and Discussion
24. Communication among Agents
24.2 Understanding Language Strings
24.4 Natural Language Processing
24.5 Additional Readings and Discussion
25.1 Three-Level Architectures
25.3 The Triple-Tower Architecture