The society of mind
Fuzzy Sets and Systems - Interpretations of Grades on Membership
The artificial intelligence debate: false starts, real foundations
The artificial intelligence debate: false starts, real foundations
Mathematical logic in artificial intelligence
The artificial intelligence debate: false starts, real foundations
The emperor's new mind: concerning computers, minds, and the laws of physics
The emperor's new mind: concerning computers, minds, and the laws of physics
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Foundations of AI: the big issues
Artificial Intelligence
AI Magazine
Inferential Theory of Learning as a Conceptual Basis for Multistrategy Learning
Machine Learning - Special issue on multistrategy learning
What is a logical system?
CYC: a large-scale investment in knowledge infrastructure
Communications of the ACM
Computer science as empirical inquiry: symbols and search
Communications of the ACM
Shadows of the Mind: A Search for the Missing Science of Consciousness
Shadows of the Mind: A Search for the Missing Science of Consciousness
Godel, Escher, Bach: An Eternal Golden Braid
Godel, Escher, Bach: An Eternal Golden Braid
AI's Greatest Trends and Controversies
IEEE Intelligent Systems
Introduction: progress in formal commonsense reasoning
Artificial Intelligence - Special issue on logical formalizations and commonsense reasoning
Problem solving with insufficient resources
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Introduction to Automata Theory, Languages, and Computation (3rd Edition)
Introduction to Automata Theory, Languages, and Computation (3rd Edition)
Rigid Flexibility: The Logic of Intelligence (Applied Logic Series)
Rigid Flexibility: The Logic of Intelligence (Applied Logic Series)
An integrated framework for learning and reasoning
Journal of Artificial Intelligence Research
Experience-grounded semantics: a theory for intelligent systems
Cognitive Systems Research
The Development of Human Expertise in a Complex Environment
Minds and Machines
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In discussions on the limitations of Artificial Intelligence (AI), there are three major misconceptions, identifying an AI system with an axiomatic system, a Turing machine, or a system with a model-theoretic semantics. Though these three notions can be used to describe a computer system for certain purposes, they are not always the proper theoretical notions when an AI system is under consideration. These misconceptions are not only the basis of many criticisms of AI from the outside, but also responsible for many problems within AI research. This paper analyses these misconceptions, and points out the common root of them: treating empirical reasoning as mathematical reasoning. Finally, an example intelligent system called NARS is introduced, which is neither an axiomatic system nor a Turing machine in its problem-solving process, and does not use model-theoretic semantics, but is still implementable in an ordinary computer.