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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

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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

    • Flounders on complex computations

    • Capable of understanding and reasoning

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


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


Related Fields

Computer

Science

Linguistics

Artificial

Intelligence

Psychology

Philosophy

Mathematics

Biology


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


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


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


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


Brain Study


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


http://www.aimovie.com


http://www.aaai.org


http://www.taai.org.tw


The Eight-Puzzle


A Puzzle-Solving Machine


Understanding Images

  • Image processing

    • Identifying characteristics

    • Edge enhancement

    • Region finding

    • Smoothing

  • Image analysis

    • Understanding what these characteristics mean


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


Portion of the 8-Puzzle’s State Graph


Applications of Production System Framework

  • Playing games of chess

  • Drawing logical conclusions from given facts


Deductive Reasoning


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


An unsolved 8-Puzzle


A Sample Search Tree


A Sample Search Tree


A Sample Search Tree


A Sample Search Tree


Productions Stack


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


Heuristic Value of An Unsolved 8-Puzzle

Heuristic value: 7 (sum of distances)


A Heuristic Algorithm


Beginning of a Heuristic Search


Search Tree After Two Passes


Search Tree After Three Passes


Complete Search Tree


A Neuron in a Living Biological System


Processing Unit


Representation of a Processing Unit


A Neural Network with Two Different Programs


Uppercase C and Uppercase T


Various Orientations of C and T


Character Recognition System


Letter C in the Field of View


The Letter T in the Field of View


Desired

Output

Actual

Output

Inputs

Adjusting Weights

Using Error

Back Propagation Network


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


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


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


A Hopfield Network


Steps Leading to a Stable Configuration


Steps Leading to a Stable Configuration


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.


Poker Strategies


Configuration of an Artificial Neural Network


Coding Artificial Neural Networks


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


Applications of Artificial Intelligence

  • Language processing

  • Robotics

  • Database systems

  • Expert systems


A Semantic Net


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