Computing Reviews: AI Classification Scheme

Here are the categories of AI from the 1998 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.

I.2 ARTIFICIAL INTELLIGENCE

I.2.0 General [Ch. 1, 2]
- cognitive simulation [Sec. 1.1]
- philosophical foundations [Sec. 1.2, Ch. 26]
I.2.1 Applications and Expert Systems (H.4, J) [throughout]
- cartography
- games [Ch. 5]
- industrial automation [Sec. 25.8]
- law [Sec. 26.3]
- medicine and science [Ch. 14.7]
- natural language interfaces [Sec. 23.3, 23.5]
- office automation [Sec. 26.3]
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 [Sec. 8.4]
I.2.3 Deducton and Theorem Proving [Part III]
- answer/reason extraction [Ch. 7, 8]
- deduction (e.g. natural, rule-based) [Ch. 7, 9]
- Inference engines [Sec. 8.4, 9.3, 9.4]
- logic programming [Sec. 9.4]
- mathematical induction [Ch. 7]
- metatheory [pg. 102]
- nonmonotonic reasoning and belief revision [Sec. 12.6]
- resolution [Sec. 7.5, 9.5]
- uncertainty, "fuzzy", and probabilistic reasoning [Part IV]
I.2.4 Knowledge Representation Formalisms and Methods [Part III]
- frames and scripts [Ch. 7]
- modal logic [pg. 451]
- predicate logic [Ch. 7]
- relation systems [Ch. 8, 12]
- representation languages [Ch. 12]
- representations (procedural and rule-based) [pg. 236]
- semantic networks [Sec. 12.5]
- temporal logic [Sec 12.3, Ch. 15]
I.2.5 Programming Languages and Software (D.3.2) [Ch. 9.4]
- expert system tools and techniques [Sec. 16.7]
I.2.6 Learning (K.3.2) [Part V]
- analogies [pg. 799]
- concept learning [Ch. 18]
- connectionism and neural nets [Sec. 18.7]
- induction [Ch. 18, 19]
- knowledge acquisition [pg. 23, 307, 860]
- language acquisition [Ch. 22, 23]
- parameter learning [Ch. 18]
I.2.7 Natural Language Processing [Ch. 22,23]
- discourse
- language generation [pg. 899]
- language models [Sec. 22.1]
- language parsing and understanding [Sec. 23.2]
- machine translation [Sec 23.4]
- speech recognition and synthesis [Sec. 23.5]
- text analysis [Ch. 22]
I.2.8 Problem Solving, Control Methods, and Search (F.2.2) [Part II, Part IV]
- backtracking [Sec. 6.3, 7.6]
- control theory [Sec. 1.2, 21.6, 25.6]
- dynamic programming [Sec. 21.2]
- graph and tree search strategies [Ch. 3,4]
- heuristic methods [Ch. 3, 4]
- plan execution, formation, generation [Ch. 10, 11]
- scheduling [Sec. 11.1]
I.2.9 Robotics [Ch. 25]
- autonomous vehicles [Sec. 25.2, 25.6]
- commercial robots and applications [Sec. 25.8]
- kinematics and dynamics [Sec. 25.6]
- manipulators [Sec. 25.3]
- operator interfaces [Sec. 25.7]
- propelling mechanisms [Sec. 25.2]
- sensors [Sec. 25.3]
- workcell organization and planning [Sec. 25.7]
I.2.10 Vision and Scene Understanding (1.4.8,1.5) [Ch. 24]
- 3D/stereo scene analysis [Sec. 24.4]
- architecture and control structures [Sec. 24.6]
- intensity, color, photometry, and tresholding [Sec. 24.1, 24.2]
- modeling and recovery of physical attributes [Sec. 24.4, 24.6]
- motion [Sec. 24.2, 24.4]
- perceptual reasoning [Ch. 24]
- representations, data structures and transforms [Ch. 24]
- shape [Sec. 24.3, 24.5]
- texture [Sec. 24.2]
- video analysis [Serc. 24.5]
I.2.11 Distributed Artificial Intelligence [Sec. 22.1]
- coherence and coordination [Sec 11.4]
- intelligent agents [Ch 2,]
- languages and structures
- multiagent systems [Sec. 11.4]

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