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CSECSE441441(Artificial Intelligence)(Artificial Intelligence)

SPU, Computer Science Dept., 1/2554

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. : B.Sc. (Math) , M.Sc. (Comp.

Science) , D.Eng. (Comp. Engineering). : 01 / : / 8.30-11.30

. / 11-0603E-mail: sukvaree.cse441@gmail.com

: 5-801 ()

Office Hour: : 8.30-11.30 . : 8.30-14.30 .

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CSE221

CSE443 (ExpertSystem)

CSE

444 ( Natural

Language Processing : NLP)CSE44

1(AI)

CSE443(ES)

CSE22

1

CSE444(NLP)

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20% 40% / 20% (quiz) 20 % 100%

1 80% 2

3

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Power Point + Lecture note : Artificial Intelligence: Modern Approach (2/ED.), by

Stuart J. Russell and Peter Norvig , ISBN:0130803022, Prentice Hall.2003.http://www.cs.berkeley.edu/~russell/ai.html http://aima.cs.berkeley.edu/

- Artificial Intelligence by Elaine Rich & Kevin Knight 2nd edition,1991, McGraw-Hill,ISBN: 0-07-052263-4.

- http://www.aaai.org/

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1 Introduction to Artificial Intelligence

2Agents and Environments, Rationality,

Agent types, AI applications.

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3 Problem Solving and SearchUninformed Search strategies

- Breadth-first-search

- Depth-first-search- Iterative deepening depth-first-search

4 Problem Solving and Search

Informed Search strategies- A* Search

- Hill climbing

- Simulated Annealing

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5Adversarial Search:- Minimax algorithm

- Alpha-Beta pruning

6 Propositional Logic

Propositional logic and Knowledge-BasedAgents

Reasoning pattern in Propositional logic

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7 First-order-logic(FOL) & Inference in FOL

- Syntax and Semantics of FOL

- Using FOL

- Unification- Resolution

8 Knowledge Representation- Frame

- Semantic Network

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10 Intro toLearning

- Forms of Learning

- Inductive Learning

- Computational Learning Theory

11 Statistical Learning:Learning with CompleteData

- Naive Bayes model

- Hidden Makov model

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12Reinforcement Learning

- Passive Reinforcement Learning

- Active Passive Reinforcement Learning

13 Neural Nets

- Units and Structure in neural network- Kernal machines

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14 Intro to NLP

- NLP level (Lexical, Syntax, Discourse,

Semantic, Pragmatic)

- NLP applications

15

15/10/2551 9:00-12:00 .

04/12/2551

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What is Artificial Intelligence

(AI)

A typical definition might be something

like this: AI is the branch ofcomputer science that deals with

making computers do things that,

were a human to do them, we would

say they required intelligence.

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Russell and Norvig

:AI is

Computational models of human

thought processes Computational models of human

behavior..

Computational systems that think

rationally.. Computational systems that behave

rationally..

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Definitions of Artificial

Intelligence:

Four Categories

Think like humans Think rationally

Act like humans Act rationally

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Acting Humanly

Computer behaves like humans

Behaviorist approach

Turing Test

MACHINE HUMAN

JUDGE

channel

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Language and Intelligence:

Turing

Test Turing test:

machine, human, and human judge

Judge asks questions ofcomputerand human.

Machines jobis to act like a human, humans jobis to convince judge that hes not the machine.

Machine judged intelligent ifit can fool judge.

Judgement ofintelligence linked to

appropriate answers to questions from thesystem.

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Thinking Rationally

Formalize the world, then use well-known

techniques to solve problems.

Mathematical logic and inference

Not the same as thinking humanly

What are the problems with this

approach?

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Acting Rationally

Beyond correct inference: Do the

right thing. Ignores what humans would do

Russell and Norvig approach:

rational agents.

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AI Applications

Medical decision support systems

Real-time speech recognizers

Robot drivers Grandmaster chess

Trade monitoring

Fraud detection Scheduling of shuttle loading