1、AI & NN Lecture Notes Chapter 10 New Progress in Intelligent Systems 10.1 Basic Review1. Fundamental Features of BNN(1) Low speed of neuronal operation: 10(2) Huge number of neurons: 10 - 10(3) Highly interconnected: 10 - 10 inputs for each neuron leading to highly parallel operation and statist

2、ically and collectively decision-making(4) Learning by connection-strength revision(5) Binary communication among neurons while analog representation within neuron(6) Output information is continuous variable- 3 Hz111234(7) Connection structure observes constraints topologically and geometrically(8)

3、 Distributed control and integrative operation(9) Proper degeneration: system performance will gradually be degraded as number of unproper neurons increases; but there does not exist a critical point at which the system performance dies out totally(10) Relaxation is the basic computation manner: by

4、iteration, the system gradually satisfies a great number of weak constraints1. Fundamental Features of BNN (Cont.)2. ANN Features(1) Large scale complex system - Many parameters adjustable(2) Parallel processing - Very rapid processing(3) Distributes storage - Associative memory and holograph(4) Fle

5、xible configuration - Better adaptive(5) High redundancy - High robustness2. ANN Feature (Cont.)(6) Non-linear operation - Self-organization, chaos, and chaos synchronous(7) Collective computation - Powerful learning(8) Non-algorithmic - Good for experimental learning(9) Simple units - Easy to imple

6、ment by VLSI3. Biological Facts not Realized in ANN(1) Some neurons are to send excitatory signals and others inhibitory, yet artificial neurons are assumed to act in both possibilities.(2) The output peak (spike) of a biological neuron has certain computational significance, but artificial neurons

7、are designed to output an average.(3) The communications among biological neurons are in diffuse manner, but in artificial neuron it is designed in a point-to-point manner.3. Biological Facts Not Realized in ANN (Cont.)(4) It was discovered recently that both the time instant and the velocity of the

8、 pulses produced by neurons are meaningful to encoding, but only the information on velocity is utilized in ANN(5) There are over 200 kinds of biological neurons, nevertheless ANN has only one kind neuron.(6) There are many different kinds of neural media biologically, however, this fact is complete

9、ly ignored in ANN.4. Comparison between ES, NN and HumansItems Man ES ANN ComputerNumeric Calculation 4 3 2 1Operation Speed 4 3 1 2Computation Accuracy 4 2 3 1Knowledge Acquisition 1 3 2 4Knowledge Expression 1 3 2 4Parallel Processing 1 3 2 4Shallow Reasoning 1 3 2 4Deep Reasoning 1 3 2 4Items Man

10、 ES ANN ComputerImprecision Reasoning 1 2 3 4Heuristic Reasoning 1 2 3 4Learning Ability 1 3 2 4Stability 1 2 4 3Robustness 1 3 2 4Mesa Effect 1 4 2 3Creative Thinking 1 4 4 44. Comparison (Cont.) 10.2 New Progress in Depth: The Trinity Theory ofInformation, Knowledge & Intelligence1. The Model

11、of Intelligence AcquisitionExecution GoalIntelligence InformationKnowledgeCognitionDecision-making Problem/Environment2. A Simplified Model of IntelligenceCognitionInformationKnowledgeIntelligenceStrategyProducingInformation RefiningKnowledge Activation3. The State-of-The-Art of Intelligence Studies

12、 Information TheoryIntelligence TheoryKnowledge TheoryC. Shannon 1948M. Minsky etal 1956?Some of The References (1) BUPT Press., 1996 Comprehensive Information Theory - Syntactic Information: Form - Semantic Information: Meaning - Pragmatic Information: UtilitySome of The References (2) PTT Press, 1

13、992The slogan “AI is dead and long live NeuralNetworks” is totally wrong. The Intelligence Theory is the entirety of AI and ANN.- The 1st CNNC in 1990 in Beijing.Some of the References (3)“The Framework of Knowledge Theory” Chinese Engineering Science, No.10, 2000also ICSCI2000, Orlando, Florida, US

14、A-Definition & Categories of Knowledge: Quality-Measurements of Knowledge: Quantity-Reasoning of Knowledge: Content-Utility of Knowledge: Value -Knowledge & Information: Knowledge Formation-Knowledge & Intelligence: Knowledge Activation4. An Approach to Intelligence CreationS-I-RP-I-RF-K

15、-FV-K-FC-K-GI-S-GPROBLEMSe-I-GInformation and Knowledge BasesConsciousness: The Kernel of IntelligenceThe object with the form has such value.Form ConsciousnessValue Consciousness Content ConsciousnessStimulusRecognitionFormValueAssessmentMeaningProducingInductive Learning and Neural NetworksWTraini

16、ngSamplesDifferenceActual OutputDesired OutputRevision Strategy10.3 New Progress in Width AI & NN Converge toMAS/DAI & Intelligent Info-NetGeneral Model of MAS/DAICACACAPAPAMAPAPAMAPAPAMAResourcesP: ProcessingC: CommunicationM: ManagingFeatures of MAS/DAI1, All databases are physically distr

17、ibuted and neither global database and nor central control.2, All agents are physically separated and linked through communication network.3, Each agent is intelligent & autonomous.4, Agents work in parallel way.5, Agents are able to cooperate and to be coordinated.6, Agents share the resources

18、available. - AI ? ANN ? after all.Large Scale Intelligent Info-NetCom-NetAgentAgentAgentFunctionalities of AgentSensingTransferringCognition & DecisionTransferringControllingTaskSocial MemberSocial ToolNew Generation ToolProductive Task 10.4 Some of The Current Trends in Intelligence ResearchInternet-Oriented Intelligent Systems1. Intelligent Search Engine2. Intelligent Article Abstraction3. High-Quality Text Translation4. Text-Voice Conversion5. Multi-Agent Cooperative SystemAll have been carried on very promisingly in Research Center of Intell