Suggested Education for Future AGI Researchers
Pei Wang[On-line document since 2008, last updated in January 2025]
The following list is a partial education plan for students interested in
the research of Artificial
General Intelligence.
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 (they are distinguished from the
others using square brackets).
- This list is not intended to cover all relevant topics, but what I think
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 or similar materials.
- Discrete Mathematics
Discrete Mathematics and Its Applications, 7/E, Kenneth Rosen
- Probability and Statistics
A Modern Introduction to Probability and Statistics, 2/E, Dekking et al.
- Computer Programming
Java How to Program, 11/E, Deitel & Associates
- Data Structure and Algorithms
Data Structures and Algorithm Analysis in Java, 3/E, Mark Allen Weiss
- Operating System
Operating System Concepts, 9/E, Avi Silberschatz et al.
- Artificial Intelligence
Artificial Intelligence: Foundations of Computational Agents, 3/E, David Poole and Alan Mackworth
- Cognitive Psychology
Cognitive Psychology, 7/E, Robert J. Sternberg et al.
- Cognitive Neuroscience
Cognitive Neuroscience: The Biology of the Mind, 5/E, Michael Gazzaniga et al.
- Cognitive Linguistics
Cognitive Linguistics：A Complete Guide, 2/E, Vyvyan Evans
- Theory of Knowledge
Knowledge: A Very Short Introduction, Jennifer Nagel
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 et al.
- Philosophical Logic
Philosophy of Logics, Susan Haack
- Decision Theory
Rationality in Action: Contemporary Approaches, Paul K. Moser
- Reasoning Under Uncertainty
Uncertain Inference, Henry E. Kyburg Jr, Choh Man Teng,
- Machine Learning
Machine Learning, Peter Flach
- Categorization
Concepts: Core Readings, Eric Margolis, Stephen Laurence
- Memory
Human Memory: Theory And Practice, Revised Edition, A.D. Baddeley
- Perception and Action
Cognitive Robotics, Angelo Cangelosi, Minoru Asada
- Developmental Psychology
Theories of Developmental Psychology, 6/E, Patricia A. Miller
- Philosophy of Science
Philosophy
of Science: The Central Issues, 2/E, J. A. Cover, Martin Curd
C. Readings on Advanced Topics
The following topic can be covered in graduate-level seminars 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
Universal Intelligence: A
Definition of Machine Intelligence, Shane Legg, Marcus Hutter
Position: Levels of AGI for Operationalizing Progress on the Path to AGI, Meredith Ringel Morris et al.
[On Defining Artificial Intelligence, Pei Wang, with Commentaries and Author’s Response]
- 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]
- Rationality
Reasoning about a rule, Wason, P. C.
Judgment under uncertainty: Heuristics and biases, Tversky, A., Kahneman, D.
Models of Bounded Rationality, Simon, H. A.
Bounded Rationality: The Adaptive Toolbox, Gigerenzer, G., Selten, R.
[The assumptions on knowledge and resources in models of rationality, 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]
- Machine learning
Deep Learning, Yann LeCun, Yoshua Bengio, Geoffrey Hinton
Deep Learning in Neural Networks: An Overview, Juergen Schmidhuber
Attention Is All You Need, Ashish Vaswani et al.
The Bitter Lesson, Rich Sutton
[Different Conceptions of Learning: Function Approximation vs. Self-Organization, Pei Wang, Xiang Li]
- Non-classical computation
Thinking may be more than computing, Peter Kugel
Approximate Reasoning Using Anytime Algorithms, Shlomo Zilberstein
Turing's Ideas and Models of Computation, Eugene Eberbach et al.
[Case-by-case 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 Hofstadter
[Problem-Solving
under Insufficient Resources, Pei Wang]
- Term logics
Term logic,
Wikipedia
Charles Sanders Peirce: Logic,
Francesco Bellucci and Ahti-Veikko Pietarinen
An
Invitation to Formal Reasoning: The Logic of Terms, Frederic Sommers,
George Englebretsen
[Toward a Logic of Everyday Reasoning, Pei Wang]
- Uncertain probabilities
Why probability probably doesn’t exist (but it is useful to act like it does), David Spiegelhalter
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
Procedural semantics, Philip N. Johnson-Laird
Contentful
Mental States for Robot Baby, Paul R. Cohen et al.
[Experience-Grounded
Semantics: A theory for intelligent systems, Pei Wang]
- Sensorimotor and 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
Action in Perception, Alva Nöe
[Perception from an AGI Perspective, Pei Wang, Patrick Hammer]
- Analogy and metaphor
The
Analogical Mind, Dedre Gentner et al.
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
[Analogy
in a general-purpose reasoning system, Pei Wang]
- Animal cognition
Animal
Minds: Beyond Cognition to Consciousness, Donald R. Griffin
The Thinking Ape: Evolutionary Origins of Intelligence, Richard Byrne
What is learning? On the nature and merits of a functional
definition of learning, Jan De Houwer et al.
Empirical Studies in Machine Psychology, Robert Johansson
[Issues in Temporal and Causal Inference, Pei Wang, Patrick Hammer]
- Planning and decision making
Robot's
Dilemma Revisited: 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.
Reinforcement Learning: An Introduction, Richard S. Sutton and Andrew G. Barto
[Assumptions of decision-making models in AGI, Pei Wang, Patrick Hammer]
- Motivation and emotion
Human Motivation, David C. McClelland
The Functional
Autonomy of Motives, Gordon W. Allport
Cognition and Motivation in Emotion, Richard S. Lazarus
Who Needs Emotions?: The Brain Meets the Robot, Jean-Marc Fellous, Michael A. Arbib
[Motivation Management in AGI Systems, The Emotional Mechanisms in NARS, Pei Wang et al.]
- Cognitive linguistics
Cognitive Linguistics: Basic Readings, Dirk Geeraerts
Language, Thought, and Logic, John M. Ellis
[Natural Language Processing by Reasoning and Learning, Pei Wang]
- Self and Consciousness
What is consciousness, and could machines have it?, Stanislas Dehaene et al.
A Cognitive Theory of Consciousness, Bernard Baars
Consciousness, Intentionality, and Causality, Walter J. Freeman
Metacognition in computation: A selected research review, Michael T. Cox
[A Constructive Explanation of Consciousness, Pei Wang]
- Cognitive architecture
Unified Theories of Cognition, Allen Newell
An Integrated Theory of the Mind, John R. Anderson, et al.
40 years of cognitive architectures: core cognitive abilities and practical applications, Iuliia Kotseruba, John K. Tsotsos
[Intelligence: From Definition to Design, Pei Wang]
- 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.
[Solving a Problem With or Without a Program, Pei Wang]
- Agent and multi-agent system
The Society of Mind, Marvin Minsky
Agent Technology: Foundations, Applications, and Markets, Nicholas R. Jennings, Michael J. Wooldridge
Agent AI: Surveying the Horizons of Multimodal Interaction, Zane Durante et al.
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, Gerhard Weiss
[From NARS to a Thinking Machine, Pei Wang]
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