[latest revision: April 30, 2008]
Suggested Education for Future AGI Researchers
Temple University, Philadelphia, USA
The following list is a partial education plan for students interested in the research of Artificial General Intelligence. It includes materials for roughly 30 one-semester courses.
Notes:
- The opinions expressed here are highly personal. Not only are the topics and reading materials selected according to my opinion, but also there are my own works included wherever relevant (they are distinguished from the others using square brackets).
- This list is not intended to cover all relevant topics, but what I think as the most important. Some crucial decisions are on what NOT to include, as well as on how to allocate time among the topics. Therefore, adding new topics into the list is not always a good idea.
Introductory Readings
The following materials can be read by anyone with a high-school education.
A. Undergraduate-level Coursework
Each of the following topic can be covered by a one-semester undergraduate course, with the recommended textbook.
- Discrete Mathematics
Discrete Mathematics and Its Applications, 6/E, Kenneth Rosen
- Probability and Statistics
A Modern Introduction to Probability and Statistics, 2/E, Dekking et al.
- Computer Programming
Java How to Program, 7/E, Deitel & Associates
- Data Structure and Algorithms
Data Structures and Algorithm Analysis in Java, 2/E, Mark Allen Weiss
- Operating System
Operating System Concepts, 7/E,
Avi Silberschatz et al.
- Cognitive Psychology
Cognitive Psychology, 4/E, Douglas Medin et al.
- Cognitive Neuroscience
Cognition, Brain, and Consciousness, Bernard J. Baars, Nicole M. Gage
- Language and Cognition
Psycholinguistics, 2/E, Jean Berko Gleason, Nan Bernstein Ratner
- Theory of Knowledge
Epistemology, Richard Feldman
- Artificial Intelligence
Artificial Intelligence: Structures and Strategies for Complex Problem Solving, 6/E, George F. Luger
B. Graduate-level Study
Each of the following topic can be covered by a one-semester graduate course (or upper-division undergraduate course), with the recommended textbook.
- Theoretical Computer Science
Introduction to Automata Theory, Languages, and Computation, 3/E,
John E. Hopcroft, Rajeev Motwani, Jeffrey D. Ullman
- Reasoning Under Uncertainty
Readings in Uncertain Reasoning, Glenn Shafer, Judea Pearl
- Machine Learning
Machine Learning, Thomas Mitchell
- Philosophical Logic
Philosophy of Logics, Susan Haack
- Decision Theory
Rationality in Action: Contemporary Approaches, Paul K. Moser
- Categorization
Concepts: Core Readings, Eric Margolis, Stephen Laurence
- Perception and Action
Sensorimotor Foundations of Higher Cognition, Patrick Haggard, Yves Rossetti, Mitsuo Kawato
- Memory
Human Memory: Theory And Practice, A.D. Baddeley
- Developmental Psychology
Theories of Developmental Psychology, 4/E, Patricia A. Miller
- Philosophy of Science
Philosophy of Science: The Central Issues, J. A. Cover, Martin Curd
C. Readings on Advanced Topics
Each of the following topic can be covered in a half-semester graduate seminar, using the listed materials.
- Research goal(s) of AI
From here to Human-Level AI, John McCarthy
Human-level artificial intelligence? Be serious!, Nils J. Nilsson
(AA)AI: more than the sum of its parts, Ronald J. Brachman
Universal Intelligence: A Definition of Machine Intelligence, Shane Legg, Marcus Hutter
[What Do You Mean by “AI”?, Pei Wang]
- Limitation of AI
Minds, machines and Gödel, J. R. Lucas
What Computers Can't Do, Hubert L. Dreyfus
Minds, Brains, and Programs, John R. Searle
The Emperor's New Mind, Roger Penrose
[Three Fundamental Misconceptions of Artificial Intelligence, Pei Wang]
- Symbolic vs. connectionist AI
Computer Science as Empirical Inquiry: Symbols and Search, Allen Newell, Herbert A. Simon
Waking Up From the Boolean Dream, or, Subcognition as Computation, Douglas Hofstadter
On the proper treatment of connectionism, Paul Smolensky
Connectionism and Cognitive Architecture: a Critical Analysis, Jerry A. Fodor, Zenon W. Pylyshyn
[Artificial General Intelligence and Classical Neural Network, Pei Wang]
- Analog models
Cybernetics, or the Control and Communication in the Animal and the Machine, Norbert Wiener
Dynamics and Cognition, Timothy van Gelder
Neural Networks and Analog Computation: Beyond the Turing Limit, Hava T. Siegelmann
- Non-classical computation
Thinking may be more than computing, Peter Kugel
Using Anytime Algorithms in Intelligent Systems, Shlomo Zilberstein
Turing's Ideas and Models of Computation, Eugene Eberbach, Dina Goldin, Peter Wegner
[Computation and Intelligence in Problem Solving, Pei Wang]
- Credit assignment and resource allocation
Principles of Meta-Reasoning,
Stuart Russell, Eric Wefald
Manifesto for an Evolutionary Economics of Intelligence, Eric B. Baum
Properties of the Bucket Brigade, John Holland
The Parallel Terraced Scan: An Optimization For An Agent-Oriented Architecture, John Rehling, Douglas Hostadter
[Problem-Solving under Insufficient Resources, Pei Wang]
- Term logics
Term logic, Wikipedia
An
Invitation to Formal Reasoning: The Logic of Terms, Frederic Sommers, George Englebretsen
[Unified Inference in Extended Syllogism, Pei Wang]
- Uncertain probabilities
Towards
a unified theory of imprecise probability, Peter Walley
Probabilistic Logic Networks, Ben Goertzel et al.
[Confidence
as Higher-Order Uncertainty, Pei Wang]
- Non-Tarskian semantics
Holism, Conceptual-Role Semantics, and Syntactic Semantics, William J. Rapaport
Logic without Model Theory, Robert Kowalski
Contentful Mental States for Robot Baby, Paul R. Cohen et al.
Procedural semantics, Philip N. Johnson-Laird
[Experience-Grounded
Semantics: A theory for intelligent systems, Pei Wang]
- Cognitive linguistics
Cognitive Linguistics: Basic Readings, Dirk Geeraerts
Language, Thought, and Logic, John M. Ellis
- Analogy and metaphor
Fluid Concepts and Creative Analogies, Douglas Hofstadter, FARG
Metaphors We Live By, George Lakoff, Mark Johnson
Case-Based Reasoning: Experiences, Lessons, & Future Directions, David B. Leake
- Embodied and situated cognition
Intelligence without representation, Rodney A. Brooks
How the Body Shapes the Way We Think: A New View of Intelligence, Rolf Pfeifer, Josh C. Bongard
The symbol grounding problem, Stevan Harnad
Perceptual symbol systems, Lawrence W. Barsalou
The Ecological Approach to Visual Perception, James J. Gibson
- Animal cognition
The Principles of Learning and Behavior, Michael Domjan
Animal Minds: Beyond Cognition to Consciousness, Donald R. Griffin
The Thinking Ape: Evolutionary Origins of Intelligence, Richard Byrne
- Agent and multi-agent system
The Society of Mind, Marvin Minsky
Agent Technology: Foundations, Applications, and Markets, Nicholas R. Jennings, Michael J. Wooldridge
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, Gerhard Weiss
- Robotics
An Introduction to AI Robotics, Robin R. Murphy
Prospects for Human Level Intelligence for Humanoid Robots, Rodney A. Brooks
Autonomous Mental Development by Robots and Animals, Juyang Weng et al.
- Reasoning about change
Robot's Dilemma: The Frame Problem in Artificial Intelligence, Zenon W. Pylyshyn
Some Philosophical Problems from the Standpoint of Artificial Intelligence, John McCarthy, Patrick J. Hayes
Reasoning about plans, James F. Allen et al.
Processes and Causality, John F. Sowa
- Motivation and emotion
Human Motivation, David C. McClelland
The Functional Autonomy of Motives, Gordon W. Allport
The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind, Marvin Minsky
Who Needs Emotions?: The Brain Meets the Robot, Jean-Marc Fellous, Michael A. Arbib
- Self
I Am a Strange Loop, Douglas R. Hofstadter
A Cognitive Theory of Consciousness, Bernard Baars
Metacognition in computation: A selected research review, Michael T. Cox
- Cognitive architecture
Unified Theories of Cognition, Allen Newell
An Integrated Theory of the Mind, John R. Anderson, et al.
- Contemporary AGI research
AGI-08 Conference papers
AGI-06 Workshop papers
AGI book chapters
[Rigid Flexibility: The Logic of Intelligence, Pei Wang]
Alternative Approaches
Instead of an AGI Textbook: wiki started by Ben Goertzel
Representative Artificial Intelligence and Cognitive Science Programs and Curricula:
- Carnegie Mellon University, Artificial Intelligence Courses
- Carnegie Mellon University, Ph.D. in Machine Learning
- Iowa State University, Courses in Artificial Intelligence
- University of Edinburgh, BSc in Artificial Intelligence & Computer Science
- University of California, San Diego, Cognitive Science, Undergraduate Courses
- University of California, San Diego, Cognitive Science, Graduate Courses
- Indiana University, Cognitive Science, Undergraduate Courses
- Indiana University, Cognitive Science, Graduate Courses
- Indiana University, Cognitive Science, Cross-Listed Courses