Artificial Intelligence: A Modern Approach

Computing Reviews: AI Classification Scheme

Here are the categories of AI from the Computing Reviews Classification Scheme published by the Association for Computing Machinery. We give [in bold] the part, chapter, section or pages in AIMA that cover each classification. (These are currently for the first edition of the text; we will update these to the second edition shortly.)

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I.2 ARTIFICIAL INTELLIGENCE

I.2.0 General [Ch. 1, 2]
- cognitive simulation [Sec. 22.1]
- philosophical foundations [Sec. 1.2, Ch. 26]
I.2.1 Applications and Expert Systems (H.4, J) [throughout]
- cartography [pg. 68, 91, 105]
- games [Ch. 5]
- industrial automation [Sec. 25.1, 25.2]
- law [pg. 29]
- medicine and science [pg. 22-27, 465]
- natural language interfaces [Sec. 23.1]
- office automation [Sec. 23.1]
I.2.2 Automatic Programming (D.1.2, F.3.1)[pg. 400]
- automatic analysis of algorithms
- program modification
- program synthesis
- program transformation
- program verification
I.2.3 Deducton and Theorem Proving [Part III]
- answer/reason extraction [Ch. 7]
- deduction (e.g. natural, rule-based) [Ch. 6, 9]
- logic programming [Ch. 10]
- mathematical induction [pg. 11]
- metatheory [pg. 140, 309, 364]
- nonmonotonic reasoning and belief revision [pg. 321, 459]
- resolution [Sec. 9.6]
- uncertainty, "fuzzy", and probabilistic reasoning [Part V]
I.2.4 Knowledge Representation Formalisms and Methods Frames and scripts [Part III]
- predicate logic [Ch. 7]
- relation systems [Ch. 10]
- representation languages [Ch. 10]
- representations (procedural and rule-based) [pg. 323]
- semantic networks [Sec. 10.6]
- connectionism [Ch. 19]
I.2.5 Programming Languages and Software (D.3.2) [Ch. 10]
- expert system tools and techniques [Ch. 10, 15]
I.2.6 Learning (K.3.2) [Part VI]
- analogies [pg. 646]
- concept learning [Ch. 18]
- connectionism and neural nets [Ch. 19]
- induction [Sec. 21.4]
- knowledge acquisition [pg. 23, 217]
- language acquisition [Sec. 23.3, 23.4]
- parameter learning [Ch. 18,19]
I.2.7 Natural Language Processing [Ch. 22,23]
- discourse [Sec. 23.6]
- language generation [pg. 657]
- language models [Sec. 22.5, pg. 686-687]
- language parsing and understanding [Sec. 22.4, 23.2]
- machine translation [Sec 23.1]
- speech recognition and synthesis [Sec. 24.7]
- text analysis [Sec. 23.1]
I.2.8 Problem Solving, Control Methods, and Search (F.2.2) Backtracking [Part II, Part IV]
- dynamic programming [pg. 87, 116, 503, 520, 603, 623, 697, 742]
- graph and tree search strategies [Ch. 3,4]
- heuristic methods [Ch. 4]
- plan execution, formation, generation [Part IV]
I.2.9 Robotics [Ch. 25]
- manipulators [Sec. 25.3]
- propelling mechanisms [Sec. 25.3]
- sensors [Sec. 25.3]
I.2.10 Vision and Scene Understanding (1.4.8,1.5) [Ch. 24]
- architecture and control structures [Sec. 25.4]
- intensity, color, photometry, and tresholding [Sec. 24.2, 24.3]
- modeling and recovery of physical attributes [Sec. 24.4, 24.6]
- motion [Sec. 24.4, 24.5]
- perceptual reasoning [Ch. 24]
- representations, data structures and transforms [Ch. 24]
- shape [Sec. 24.4]
- texture [Sec. 24.4]
I.2.11 Distributed Artificial Intelligence [Sec. 22.1]
- coherence and coordination [Sec 22.1, 22.9]
- languages and structures [Sec. 22.1]

AI: A Modern Approach by Stuart Russell and Peter Norvig Modified: Dec 31, 2002