1 New Y. X. Zhong Chinese Association for AI (CAAI) University of Posts & Telecom, Beijing -- to The Celebration of The 50 th Anniversary of AI Stage Problems Approach Proposal New

2 List of Contents 2, New Problems 3, New Approach 4, New Proposal 1, Introduction

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4 The 50 th Anniversary of The Birth of AI A good time for AI researchers worldwide to review what happened in the past 50 years, to analyze what will happen in the future, and to discuss what and how we should do next.

5 2, New Problems -- Inconsistent approaches and New demand

6 The Structuralism Approach 1943, McCulloch-Pitts: Logic Model of Nerve Cell. 1981, Hopfield: New Model and Learning Algorithm of Neural Networks 1990, Computational Intelligence -- Neural Networks -- Fuzzy Logic -- Evolution Computing -- Chaotic Theory -- Rough Set Theory

7 The Functionalism Approach 1956, Newell, Simon et al Logic Theorist, GPS, Means-Ends Analysis 1970, Feigenbaum et al Expert Systems (Knowledge Engineering) 1990 Hybrid Systems Data Mining and Knowledge Discovery Fuzzy Set Theory Machine Learning Multi-Agent System

8 The Behaviorism Approach 1990, Brooks: Intelligence without Representation; 1991, Brooks: Intelligence without Reasoning Pattern Recognition Action Response Effectiveness

9 Brief Comments 1, All have made great progresses while facing critical difficulties. 2, All are independent to each other and lack of coordination. 3, It leaves questions: What is the relationship among the three? Are there any better approaches to AI ?

10 NewNew New Demand from Intelligence Research Emotion and Artificial Emotion Consciousness and Artificial Consciousness Cognitive Informatics Artificial Life Intelligent Robot Intelligent Agent, multi-Agent and Distribute AI Complex Systems and Intelligent Information Network Natural Intelligence

11 3, New Approach -- A better approach to AI

12 Mechanism Approach to AI Structure, function and behavior of intelligent systems can provide some meaningful information on intelligence though a deeper insight approach to AI research should be concerned with the mechanism of intelligence formation. Structure Behavior Function Mechanism

13 Mechanism Model on Human Intelligence Acquisition Transferring Cognition Execution Real World Decision Transferring Acquired Information Knowledge Intelligent Strategy Intelligent ActionOriginal Information Processing Processed Information

14 Core Mechanism of Intelligence Formation InformationKnowledgeIntelligence Cognition Decision Making Transformations from information to knowledge and further to intelligence are the keys.

15 New Concept & Theory Needed (1) Comprehensive Information Theory (Y. X. Zhong, ) SymbolObjectSubject Formal Description Syntactic Meaning SemanticPragmatic Utility States x 1 x n x N Certainty c 1 c n c N Truth t 1 t n t N Utility u 1 u n u N

16 Where  n  c n )·(  t n )·(  u n )

17 New Concept & Theory Needed (2) Knowledge Theory (Y. X. Zhong, 2000) -- Definition: Description about a class of events on their states at which the events may stay and the law by which the states may vary. -- Categorization: formal, content, value -- Representation: p (possibility), r (rationality), v (value) States x 1 x n x N Possibility p 1 p n p N Rationality r 1 r n r N Value v 1 v n v N

18 Where  n  p n )·(  r n )·(  v n ) -- Measures: K(P, P*;U), K(R, R*;U), K(V,V*;U)

19 Inherent Knowledge Empirical Knowledge Regular Knowledge Commonsense Knowledge -- Ecology of Knowledge Growth

20 Algorithms: Information  Knowledge Information Empirical Knowledge Regular Knowledge Induction Learning Validation/Deduction Popularization CSK-1 Base Common Sense Knowledge-2 Common Sense Knowledge-1 Information

21 Algorithms: Knowledge  Intelligence Neural Network Expert System Sensor-Motor Empirical Knowledge Regular Knowledge Common Sense Knowledge Intelligent Strategy Intelligent Strategy Intelligent Strategy

22 All Algorithms Are Feasible and Open Algorithms for Knowledge  Intelligence Transformation -- Experience-Based: Neural Networks and the like -- Regular K-Based: Expert Systems -- Common K-Based: Senor-Motor Algorithms for Information  Knowledge Transformation -- information  experience: Induction Algorithms (Data-Mining, Knowledge Discovery, …) -- old knowledge  new one: Deduction Algorithms (Logic Reasoning, Rough Set Theory…) -- RK  common knowledge: popularization Algorithms for Interfaces: All are interoperable.

23 Sensor-Motor Validation Expert System Neural Network P-C-G A Unified Model of AI InformationKnowledgeIntelligence I-Action Acquisition Execution Popularization E.K R.K C.K C.K-2 C.K

24 ConversionDM I-Strategy G Cognition K CI K-Base Retrieval Reflection CSK-Base Syntactic Info CSK-Cons. Emotion Information Consciousness-Emotion-Intelligence

25 Implications & Open Problems 1, Instead of being contradictory among the three, AI Theory is now becoming a big and harmonious family, a unified and systematic discipline, thus gaining greater momentum. 3, The unified theory of AI does not close the door but rather, it opens up more future works: -- Specific algorithms in all possible applications -- More Challenges: Implicit Intelligence – finding and defining problems 2, As results, AI should now mean the trinity of traditional AI, neural network (Computational Intelligence) and the senor- motor systems.

26 4, New Proposal -- International Studies on Advanced Intelligence

27 Should We Need To Prepare A New Platform? Advanced Intelligence: Natural Intelligence - Machine Intelligence (NN+ES+SM) Intelligence-Emotion-Consciousness-Cognition Complex System-Distributed Intelligence-Intelligent Web International Platform on Advanced Intelligence (IPAI): A New Platform for Conference on Advanced Intelligence. Basic Principles for IPAI: Freedom: For freely exchanging ideas and sharing progress. Free in and free out. Equity: All individuals are equal in IPAI. Democracy: Representatives of regions as operational body Host: in turn via Application

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