Suggested Education for Future AGI Researchers

Pei Wang

The following list is a partial education plan for students interested in the research of Artificial General Intelligence. It includes materials for roughly 25 one-semester courses.

Notes:

1. 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).
2. 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.

• Computing machinery and intelligence, Alan M. Turing
• Gödel, Escher, Bach: An Eternal Golden Braid, Douglas R. Hofstadter

A. Undergraduate-level Coursework

Each of the following topic can be covered by a one-semester undergraduate course, with the recommended textbook.

1. Discrete Mathematics
   Discrete Mathematics and Its Applications, 7/E, Kenneth Rosen
2. Probability and Statistics
   A Modern Introduction to Probability and Statistics, 2/E, Dekking et al.
3. Computer Programming
   Java How to Program, 7/E, Deitel & Associates
4. Data Structure and Algorithms
   Data Structures and Algorithm Analysis in Java, 2/E, Mark Allen Weiss
5. Operating System
   Operating System Concepts, 9/E, Avi Silberschatz et al.
6. Artificial Intelligence
   Artificial Intelligence: Structures and Strategies for Complex Problem Solving, 6/E, George F. Luger
7. Cognitive Psychology
   Cognitive Psychology, 6/E, Robert J. Sternberg, Karin Sternberg
8. Cognitive Neuroscience
   Cognitive Neuroscience: The Biology of the Mind, 5/E, Michael Gazzaniga, Richard B. Ivry, George R. Mangun Ph.D.
9. Cognitive Linguistics
   Cognitive Linguistics：A Complete Guide, 2/E,  Vyvyan Evans
10. Theory of Knowledge
    Epistemology, Richard Feldman

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.

1. Theoretical Computer Science
   Introduction to Automata Theory, Languages, and Computation, 3/E, John E. Hopcroft, Rajeev Motwani, Jeffrey D. Ullman
2. Philosophical Logic
   Philosophy of Logics, Susan Haack
3. Decision Theory
   Rationality in Action: Contemporary Approaches, Paul K. Moser
4. Reasoning Under Uncertainty
   Uncertain Inference, Henry E. Kyburg Jr, Choh Man Teng,
5. Machine Learning
   Machine Learning, Peter Flach
6. Categorization
   Concepts: Core Readings, Eric Margolis, Stephen Laurence
7. Memory
   Human Memory: Theory And Practice, Revised Edition, A.D. Baddeley
8. Perception and Action
   Cognitive Robotics, Angelo Cangelosi, Minoru Asada
9. Developmental Psychology
   Theories of Developmental Psychology, 6/E, Patricia A. Miller
10. Philosophy of Science
    Philosophy of Science: The Central Issues, 2/E, J. A. Cover, Martin Curd

C. Readings on Advanced Topics

Each of the following topic can be covered in a graduate seminar for roughly a month, using the listed materials.

1. 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
   [On Defining Artificial Intelligence, Pei Wang, with Commentaries and Author’s Response]
2. 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]
3. 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]
4. Machine learning
   Deep Learning, Yann LeCun, Yoshua Bengio, Geoffrey Hinton
   Deep Learning in Neural Networks: An Overview, Juergen Schmidhuber
   Mastering the game of Go with deep neural networks and tree search, David Silver et al.
   [Different Conceptions of Learning: Function Approximation vs. Self-Organization, Pei Wang, Xiang Li]
5. 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, Dina Goldin, Peter Wegner
   [Case-by-case Problem Solving, Pei Wang]
6. 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]
7. Term logics
   Term logic, Wikipedia
   An Invitation to Formal Reasoning: The Logic of Terms, Frederic Sommers, George Englebretsen
   [Non-Axiomatic Logic: A Model of Intelligent Reasoning, Pei Wang]
8. 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]
9. 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]
10. 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]
11. Analogy and metaphor
    The Analogical Mind, Dedre Gentner, Keith J. Holyoak, Boicho K. Kokinov
    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]
12. 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
    [Issues in Temporal and Causal Inference, Pei Wang, Patrick Hammer]
13. 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]
14. 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
    [Motivation Management in AGI Systems, The Emotional Mechanisms in NARS, Pei Wang]
15. Cognitive linguistics
    Cognitive Linguistics: Basic Readings, Dirk Geeraerts
    Language, Thought, and Logic, John M. Ellis 
    [Natural Language Processing by Reasoning and Learning, Pei Wang]
16. Self and Consciousness
    A Cognitive Theory of Consciousness, Bernard Baars
    Metacognition in computation: A selected research review, Michael T. Cox
    Consciousness, Intentionality, and Causality, Walter J. Freeman
    [Self in NARS, an AGI System, Pei Wang, Xiang Li, Patrick Hammer]
17. Cognitive architecture
    Unified Theories of Cognition, Allen Newell
    An Integrated Theory of the Mind, John R. Anderson, et al.
[Rigid Flexibility: The Logic of Intelligence, Pei Wang]
18. 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]
19. 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
    [From NARS to a Thinking Machine, Pei Wang]
20. Contemporary AGI research
    Conferences
    Collections: 2007 , 2012
    Journal: JAGI
    [Theories of Artificial Intelligence: Meta-theoretical considerations, Pei Wang]