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Knowledge Theory & A Unified Theory of AI

Knowledge Theory & A Unified Theory of AI. Y. X . Zhong Univ. of Posts & Telecom, Beijing yxzhong@ieee.org. List of Contents. 1, Fundamentals of Knowledge Theory. 2, How Is KT Crucial To AI?. Knowledge Theory: Fundamentals. Functional Definition of Knowledge.

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Knowledge Theory & A Unified Theory of AI

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  1. Knowledge Theory &A Unified Theory of AI Y. X . Zhong Univ. of Posts & Telecom, Beijing yxzhong@ieee.org

  2. List of Contents 1, Fundamentals of Knowledge Theory 2, How Is KT Crucial To AI?

  3. Knowledge Theory:Fundamentals

  4. Functional Definition of Knowledge Knowledge is something that can be used for answering certain questions. The basic question is the standard alternative problem with 2n equally-possible answers, n>1. Its amount of question is defined as n unit of the amount of question – n alt. 1/2 A Standard Alternative Question 1/2 If a piece of knowledge can exactly answer one of such questions, the amount of the knowledge is defined as n unit of the amount of knowledge – n alt.

  5. Descriptive Definition of Knowledge Knowledge is a description of a class of events on -- their statesat which the events may stay and -- the lawthe states may vary from one to another. S(2) S(1) S(n)

  6. Representation of Knowledge The key elements for knowledge representation are (1) The States (2) The Relationship among The States Give ISA Giver John G1 B23 Object Recipient ISA Book Mary “John gives Mary the book”

  7. General Representation of Knowledge Large-scale, Multi-Branch, Hierarchical, Dynamic and Interacted Complex Network with Weights Concept is the Element of knowledge.

  8. Relation between Knowledge & Information Epistemological Information is the description of an event on its states at which the events may stay and the mannerthe states may vary from one to another. Compared with the definition of the epistemological information, it is found that knowledge is the result of the epistemological information refining (induction): States– States Manner of State Varying– Law of State Varying

  9. Categorization of Knowledge It might be reasonable to classify the knowledge in accordance with the branches of science & Technology. But, it will be meaningless for Knowledge Theory research. Instead, knowledge is suggested to classify into formal, content, and value components Representation:p (possibility), r (rationality), v (value) States x1 xn xN Possibility p1 pn pN Rationality r1 rn rN Value v1 vn vN

  10. Measures of Knowledge Amount K(P, P*;U), K(R, R*;U), K(V,V*;U) Where n = (pn)·(rn)·(vn)

  11. Internal Ecosystem of Knowledge Growth Empirical Knowledge Regular Knowledge Commonsense Knowledge Inherent Knowledge

  12. External Ecosystem of Knowledge Decision Making Cognition Information Knowledge Intelligence Knowledge is the crucial gateway for linking Information on one hand and intelligence on the other.

  13. Information-Knowledge Transformation (Knowledge Discovery) General Algorithms Syntactic Information Induction Formal Knowledge Deduction Semantic Content Knowledge Pragmatic Information Induction Value Knowledge Goal

  14. Knowledge-Intelligence Transformation: Algorithms in Principle G Information On P & C Deduction/ Induction Algorithms Intelligent Strategy Knowledge Base

  15. Knowledge-Intelligence Transformation Algorithm More Specific Comparison & Distance Computing Goal KB Analysis Inference Computation Intelligent Strategy Constraints Problem

  16. 2, How Is KT Crucial to AI?

  17. KT and The Unified AI C.K-1 Sensor-Motor C.K Neural Network Acquisition Execution E.K I-Action Validation P-C-G R.K Expert System R.K Popularization C.K-2 Information Knowledge Intelligence

  18. Framework & Algorithms Are Feasible Algorithms forInformation  Knowledge Transformation --information  experience:Induction Algorithms (PR, Data-Mining, Knowledge Discovery, …) --old knowledge  new one: Deduction Algorithms (Logic Reasoning, Rough Set Theory…) --Regular K  Common knowledge:popularization Algorithms forKnowledge  Intelligence Transformation -- Experience-Based: Neural Networks and the like -- Regular K-Based: Expert Systems -- Common K-Based: Senor-Motor

  19. Implications & Open Problems

  20. 1, Knowledge Theory is important because it is a midway to intelligence. Intelligence Theory is important because it is the ability to solve problems (Macro Ecosystem). 2, Due to the knowledge ecology (Micro Ecosystem),AI should mean the trinity (Unification) of traditional AI, Computational Intelligence and senor-motor systems. 3, The transformation of information-knowledge-intelligence will play a central role in the development of science and technology in formation age as that of energy conversion in industrial age.

  21. Thank You for Comments !

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