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Artificial Intelligence Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication Engineering National Taiwan University Computer vs. Human Machine Performs precisely defined tasks with speed and accuracy Not gifted with common sense Human

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Artificial intelligence l.jpg

Artificial Intelligence

Shyh-Kang Jeng

Department of Electrical Engineering/

Graduate Institute of Communication Engineering

National Taiwan University


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Computer vs. Human

  • Machine

    • Performs precisely defined tasks with speed and accuracy

    • Not gifted with common sense

  • Human

    • Flounders on complex computations

    • Capable of understanding and reasoning

    • More likely to understand the results and determine what to do next


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Humanlike Computer

  • Continue without human intervention when faced with unforeseen situations

  • Possesses or simulate the ability to reason

  • Psychologists and their models may be helpful


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Related Fields

Computer

Science

Linguistics

Artificial

Intelligence

Psychology

Philosophy

Mathematics

Biology


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監控認知系統

覺知

指揮

知識系統

表徵、儲存

重整、合成

認知策略系統

學習與記憶

思考與解題

No

新知識

或策略

動作系統

Yes

Yes

有限的訊息傳遞系統

事件記憶(長期)

事件記憶(短期)

注意與辨識

行為反應

感覺的訊息登錄

訊息刺激


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Two Approaches

  • Performance oriented

    • Computer scientists’ main concern

    • Build more useful machines

  • Simulation oriented

    • Psychologists’ focus

    • Understanding human thought and behavior

    • Opportunities to test theories


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Weak AI vs. Strong AI

  • Weak AI

    • Machines programmed to exhibit intelligent behavior

    • Games and expert systems

  • Strong AI

    • Machines programmed to possess intelligence and consciousness

    • Intelligence and consciousness are internal characteristics that can not be identified directly


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Evaluating Intelligent Behavior of Machines

  • Turing test

    • A human interrogator communicates with a test subject by means of a typewriter system

    • A machine behaves intelligently if the interrogator can not distinguish it from a human

  • Programs DOCTOR and Eliza

    • ftp://ftp.cc.utexas.edu/depts/AI_ATTIC/Programs/Classic/Eliza/Eliza-pc/eliza1.zip



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How Brains Think?

Cognition 認知

Emotions 情緒

Being, Insight 存在感、洞察力

?

Neurons 神經元

Synapses 突觸

Membranes 細胞膜

Bio Chemistry 生物化學

Chemical Bonds 化學鍵

Quantum Mechanics 量子力學







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Understanding Images

  • Image processing

    • Identifying characteristics

    • Edge enhancement

    • Region finding

    • Smoothing

  • Image analysis

    • Understanding what these characteristics mean


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Production System

  • Encloses common characteristics of reasoning problems

  • Major components

    • A collection of states

      • Start state and goal state

    • A collection of productions (rules or moves)

      • Production is an operation that can be performed to move from one state to another

    • A control system

      • Decides which production should be applied next


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Portion of the 8-Puzzle’s State Graph


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Applications of Production System Framework

  • Playing games of chess

  • Drawing logical conclusions from given facts



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Search Trees

  • Control system

    • Searches the state graph to find a path from the start node to the goal

  • A strategy is to build a search tree

    • Root: start state

    • Children: states reachable by applying one production

    • Walking up the tree from the goal




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A Sample Search Tree


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A Sample Search Tree


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A Sample Search Tree



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Tree-Searching Strategies

  • Breadth-first search

  • Depth-first search

  • Heuristics

    • Constitute a reasonable estimate of the amount of work remaining in the solution if the associated state were reached

    • Easy to compute


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Heuristic Value of An Unsolved 8-Puzzle

Heuristic value: 7 (sum of distances)
















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Desired

Output

Actual

Output

Inputs

Adjusting Weights

Using Error

Back Propagation Network


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Associative Memory

  • Retrieval of information that is associated with, or relevant to, the information at hand

  • Implementation by Artificial Neural Network

    • Processor units are interconnected to form a web with no inputs or outputs


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Stable and Unstable Configurations

  • Each unit can be in its excited or inhibited state

  • Certain configurations are stable in the sense that when the network finds itself in one of these configurations, it will remain in that configuration

  • If the network is in a non-stable configuration, then the interaction of the processing units will cause the configuration to change


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Association of Information

  • When given a part of a stable configuration, the network is able to complete the configuration

  • Or, it is able to find the bit pattern that is associated with the partial pattern it is given





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Genetic Algorithms

  • Apply our knowledge of natural evolution to problem-solving

  • Algorithm

    • Represents potential solutions as strings of symbols

    • A collection of potential solutions is generated and tested

    • The better examples from the collection are crossed to form a new generation of potential solutions. Sometimes a mutation is added.





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Evolutionary Programming

  • Develop programs by allowing them to evolve rather than by explicitly writing them

  • An important step is to find ways in which parts of programs can be interchanged to produce meaningful new programs

  • The functional programming paradigm has proved useful in this context


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Applications of Artificial Intelligence

  • Language processing

  • Robotics

  • Database systems

  • Expert systems



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