Talk:Artificial intelligence/Textbook survey

These are listed on the [http://aima.cs.berkeley.edu/books.html list of textbooks at AI Topics], which also lists their relative popularity. These are the four most popular textbooks published since 1998 (i.e. in the ten years before this survey was done.)

{{Russell Norvig 2003}}

Chapters:

• 1 Introduction History of AI, some philosophy of AI
• 2 Intelligent agent paradigm
• 3-6 Search
• 7-9 Logic
• 10 Knowledge representation
• 11-12 Planning
• 13-17 Uncertain reasoning
• 18-21 Learning
• 22-23 Natural language processing (they call "communication")
• 24 Perception
• 25 Robotics
• 26 Philosophy of AI
• 27 future of AI

{{Citation|last=Nilsson|first=Nils|author-link=Nils Nilsson|year=1998|title=Artificial Intelligence: A New Synthesis|publisher=Morgan Kaufmann Publishers|isbn=978-1-55860-467-4}}

:1 Introduction

I Reactive Machines

:2 Stimulus-Response Agents

:3 Neural Networks

:4 Machine Evolution

:5 State Machines

:6 Robot Vision

II Search in State Spaces

:7-9 search, uninformed, heuristic

:10 Planning, Acting, and Learning chapter is actually mostly about search, I think...

:11 Alternative Search Formulations and Applications

:12 Adversarial Search

III Knowledge Representation and Reasoning

:13-16 The Propositional, Predicate Calculus and resolution

:17 Knowledge-Based Systems

:18 Representing Commonsense Knowledge

:19 Reasoning with Uncertain Information

:20 Learning and Acting with Bayes Nets

IV Planning Method Based on Logic

:21 The Situation Calculus

:22 Planning

V Communication and Integration

:23 Multiple Agents

:24 Communication Among Agents Natural Language Processing

:25 Agent Architectures

• {{Citation|first=George|last= Luger |first2=William|last2= Stubblefield|year=2004|title=Artificial Intelligence: Structures and Strategies for Complex Problem Solving|edition=5th|publisher=The Benjamin/Cummings Publishing Company, Inc.|pages= 720|isbn=0-8053-4780-1|url=http://www.cs.unm.edu/~luger/ai-final/tocfull.html}}
• 1 ARTIFICIAL INTELLIGENCE: ITS ROOTS AND SCOPE 1
• 2 THE PREDICATE CALCULUS 45
• 3-4 STRUCTURES AND STRATEGIES FOR STATE SPACE SEARCH 79 (including Hill Climbing and Dynamic Programming)
• 5 STOCHASTIC METHODS 165
• 6 CONTROL AND IMPLEMENTATION OF STATE SPACE SEARCH 193
• 7 KNOWLEDGE REPRESENTATION 227
• 8 STRONG METHOD PROBLEM SOLVING (Expert systems) 277
• 9 REASONING IN UNCERTAIN SITUATIONS 333
• 10-12 MACHINE LEARNING: SYMBOL-BASED 387 / CONNECTIONIST 453 / SOCIAL AND EMERGENT 507 (including: Genetic, classifier, artificial life)
• 13 AUTOMATED REASONING 547
• 14 UNDERSTANDING NATURAL LANGUAGE 591
• 15 PROLOG 636
• 16 AN INTRODUCTION TO LISP 723
• 17 ARTIFICIAL INTELLIGENCE AS EMPIRICAL ENQUIRY 823

{{Citation | first = David | last = Poole | first2 = Alan | last2 = Mackworth | first3 = Randy | last3 = Goebel | publisher = Oxford University Press | publisher-place = New York | year = 1998 | title = Computational Intelligence: A Logical Approach | url = http://www.cs.ubc.ca/spider/poole/ci.html | author-link=David Poole }}

• Chapter 1 Computational Intelligence and Knowledge introduction
• Chapter 2 A Representation and Reasoning System forward and backward chaining
• Chapter 3 Using Definite Knowledge ''includes databases and natural language
• Chapter 4 Searching includes standard state space searches, dynamic programming, constraint satisfation, hill climbing, "randomization algortihms" and genetic algorithms
• Chapter 5 Representing Knowledge
• Chapter 6 Knowledge Engineering,
• Chapter 7 Beyond Definite Knowledge includes first order logic, proof systems
• Chapter 8 Actions and Planning
• Chapter 9 Assumption-Based Reasoning, default reasoning, abduction
• Chapter 10 Using Uncertain Knowledge
• Chapter 11 Learning
• Chapter 12 Building Situated Robots

{{Citation|first= Elaine|last= Rich|first2=Kevin |laast2=Knight|title=Artificial Intelligence|edition=2nd|publisher=McGraw-Hill|location= New York|year=1991|isbn= 0-07-052263-4|url=http://greta.cs.ioc.ee/yik/lib/22/Rich1.html}}

• What is Artificial Intelligence?
• Problems, Problem Spaces, and Search. Heuristic Search Techniques.
• Knowledge Representation. Knowledge Representation Issues.
• Using Predicate Logic. Representing Knowledge Using Rules.
• Symbolic Reasoning Under Uncertainty. Statistical Reasoning.
• Weak Slot-and-Filler Structures. Strong Slot-and-Filler Structures. Knowledge Representation Summary.
• Game Playing.
• Planning.
• Understanding.
• Natural Language Processing.
• Parallel and Distributed AI.
• Learning.
• Connectionist Models.
• Common Sense.
• Expert Systems.
• Perception and Action.
• Conclusion.

{{Citation|last=Cawsey|first=Alison|year=1998|title=Essence of Artificial Intelligence|publisher=Prentice Hall|url=http://www.cee.hw.ac.uk/%7Ealison/essence.html|isbn=0135717795}}

• Introduction.
• Knowledge Representation and Inference.
• Expert Systems.
• Using Search in Problem Solving.
• Natural Language Processing.
• Vision.
• Machine Learning and Neural Networks.
• Agents and Robots.

{{Citation|last=Murray|first=Arthur|year=2002|title=AI4U|publisher=iUniverse|isbn=0595259227}}

• Introduction.
• 1-34 Modules of the AI Mind; Exercises.
• JavaScript source code of the tutorial AI Mind.

Artificial Intelligence: Foundations of Computational Agents

: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 Learning

::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

:Part I: Foundations

::1. History, motivations, and core themes

::2. Philosophical foundations

::3. Philosophical challenges

:Part II: Architectures

::4. GOFAI

::5. Connectionism and neural networks

::6. Dynamical systems and embedded cognition

:Part III: Dimensions

::7. Learning

::8. Perception and computer vision

::9. Reasoning and decision making

::10. Language and communication

::11. Actions and agents

::12. Artificial emotions and machine consciousness

:Part IV: Extensions

::13. Robotics

::14. Artificial life

::15. The ethics of artificial intelligence

{{Citation|last=ACM|first=(Association of Computing Machinery) |year=1998|title=ACM Computing Classification System: Artificial intelligence|url=http://www.acm.org/class/1998/I.2.html |author-link=Association of Computing Machinery}}

• I.2.0 General
• I.2.1 Applications and Expert Systems (H.4, J) considered in this in the section "Applications"
• I.2.2 Automatic Programming (D.1.2, F.3.1, F.4.1) not considered AI by wikipedia
• I.2.3 Deduction and Theorem Proving (F.4.1)
• I.2.4 Knowledge Representation Formalisms and Methods (F.4.1)
• I.2.5 Programming Languages and Software (D.3.2)
• I.2.6 Learning (K.3.2)
• I.2.7 Natural Language Processing
• I.2.8 Problem Solving, Control Methods, and Search (F.2.2) control theory, dynamic programming, search, planning & scheduling
• I.2.9 Robotics
• I.2.10 Vision and Scene Understanding (I.4.8, I.5)
• I.2.11 Distributed Artificial Intelligence

{{Citation|last=Sloman|first=Aaron|year=2007|title=Artificial intelligence: an illustrative overview|url=http://www.cs.bham.ac.uk/%7Eaxs/courses.ai.html|publisher=University of Birmingham}}

• Perception
• Natural language processing
• Learning
• Planning, problem solving, automatic design
• Varieties of reasoning
• Study of representations (knowledge representation)
• Memory mechanisms and techniques
• Multi agent systems
• Affective mechanisms
• Robotics
• Architectures for complete systems.
• Search
• Ontologies

{{Citation|last=Leake|first=David B.|year=2002|contribution=Artificial intelligence|title=Van Nostrand Scientific Encyclopedia|edition=ninth|publisher=Wiley|location=New York|url=http://www.cs.indiana.edu/%7Eleake/papers/p-01-07/p-01-07.html}}

• Knowledge capture, representation and reasoning
• Reasoning under uncertainty
• Planning, Vision, and Robotics
• Natural language processing
• Machine Learning

This table lists (just about) every topic that appears in the title of a section or in a chapter summary of {{Harvtxt|Russell|Norvig|2003}}, the most popular AI textbook. Information for the other textbooks is based on their tables of contents, available online. Several topics appear more than once, in different contexts.

{{reflist}}

---- CharlesGillingham (talk) 00:05, 30 November 2007 (UTC)