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인공지능 Week 1 : Introduction

인공지능 Week 1 : Introduction. 강의내용. 학문 vs. 기술 vs. 철학적인 문제 들 인공지능의 고전적이고 기본적인 이론들 탐색 지식표현과 추론 학습과 예측 … IT 기술의 최근 이슈에 대한 조사 향후 변화된 상황에서의 새로운 이슈들과 남겨진 문제들. 강의 운영 방법. 수업 : 이론 및 실습 이론 : AI, Data Mining, Search 등 실습 : 탐색방법 : C 나 Java

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인공지능 Week 1 : Introduction

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  1. 인공지능Week 1 : Introduction

  2. 강의내용 • 학문 vs. 기술 vs. 철학적인 문제들 • 인공지능의 고전적이고 기본적인 이론들 • 탐색 • 지식표현과 추론 • 학습과 예측 … • IT기술의 최근 이슈에 대한 조사 • 향후 변화된 상황에서의 새로운 이슈들과 남겨진 문제들

  3. 강의 운영 방법 • 수업 : 이론 및 실습 • 이론 : AI, Data Mining, Search 등 • 실습 : • 탐색방법 : C나 Java • 지식표현 및 추론 : Lisp + KM(Knowledge Machine) • 데이터마이닝: SPSS, Clementine 등 . • 발표 : 주제 및 최근 이슈에 관한 조사 발표 • 개인과제 및 팀 프로젝트 • 팀 멤버는 3~4명

  4. 평가방법 상대평가 구간 • 반영비율 • 개인 성취율: • 중간고사: 30% • 기말고사: 30% • 과제 및 팀 프로젝트 : 30% • 출석 및 수업참여도 : 10% • (변경될 수 있음.)

  5. Week 1 ~ 2 : AI Introduction

  6. What is Artificial Intelligence? Study of how to make Computers do things which (at the moment) people do better Vague? Different View Points Engineering, Science, Philosophy

  7. Artificial Intelligence: Definition McCarthy ‘the science and engineering of making intelligent machine, especially intelligent computer programs ‘using computers to understand human intelligence’

  8. What is Intelligence? • Aspects of Intelligence • problem solving • memorize logical reasoning , intuition, judgment, creativity … • learning commonsense.. • emotion, cognition, love, hate,.. etc. • What is intelligence? • we know it when we see it (relative concept) • What is the most basic intelligence?

  9. Turing Test • Ultimate Intelligence: Turing suggested • Imitation Game (next slide) • Intelligent as much as Human • Is dog intelligent ? • Any man-made system passed Turing Test ? -- Any Examples in SF Movie?

  10. Imitation Game

  11. Intelligent System Cognition Understanding Judgment Flexible Automated Optimized 

  12. AI : Engineering Aspects • Making Computer (or IT Systems) more Intelligent –better performance (performance? ) • Making Machines more User Friendly • Making a Thinking Machine : Robot • Can machine think ?

  13. Examples of AI Systems Intelligent Home Appliances Intelligent Building HCI (Human Computer Interaction) Intelligent Traffic Control Robots Voice, Character Recognition Ubiquitous System

  14. Cognitive Science Program(algorithm) = mind? Mind Model Is mind a chemical reaction? In Search of Semantics Can Machine have a Mind? Artificial Intelligence Psychology Neuro-Science Linguistics Philosophy

  15. Brief History of AI • ’80 • Expert Systems –Mycin, Prospector • Neural Net • ’90 - Present • Software Agent, Data Mining • Semantic Web • Ontology • ’50 • 1956 – Dartmouth Conference • MaCarthy, Minsky, Newell • Lisp • 60 • GPS(General Problem Solver) – Newell • Chess Programs • ’70 • Theorem Proving – resolution(Robinson) • Prolog

  16. Success / Failure • Sad Story of Machine Translation • Compiler : Programming Language • Can you do the same to human language? • “time flies like an arrow” • Bonanza • Prospector : first AI system of commercial success • Challenge == Machine Understanding!!

  17. AI Impact • Programming Language • Lisp, Prolog, Object Oriented Language • Database • Knowledge-base, Ontology, NL Query • Internet • Semantic web, XML • Network • Ubiquitous, Bio-Informatics, etc.

  18. Approaches of AI Systems Knowledge-based Approach (Top Down, Deduction, Symbolic) u Data Driven Approach (Bottom Up, Induction, Network) u

  19. Knowledge-based System Represent Human knowledge as symbol combination (Rule) u Knowledge Acquisition and Representation Deductive System u Logic, Expert System, Fuzzy Logic

  20. Data Driven Approach Extract common characteristics from collected examples(data) u Training(Correct/Incorrect Data) u Statistical Method, Artificial Neural Network Data Mining

  21. Generality vs Performance • Trade off • Initial Attempts  General Problem Solving (Failure) Complexity : Toy Problems Only • Recent AI Systems: Specialized Approach • Knowledge Based Approach • Expert Systems • Machine Translation

  22. Human vs AI Technology • Brain • - Knowledge Representation • - Reasoning/ Planning • - Machine Learning • Other • - Natural Language • - Speech Recognition Eye - Vision, Character Recognition Mouth - Speech Generation Arms Legs - Robot Arms, Autonomous Vehicle - Intelligent Agent, Softbot

  23. Research Areas Symbolic Programming Knowledge Representation Search & Planning Automated Reasoning Machine Learning/ Data Mining Artificial Neural Net Ontology

  24. AI : Future • Application of AI Technology • Smart Home • Web Auto Translation System • Voice Recognition/ Intelligent HCI • Unified Paradigm • Symbolic Processing + Neural Processing • Knowledge-based + Data Driven

  25. AI : Future AI in everywhere, AI in nowhere  Ubiquitous Systems Softbot (Software Robot) Human Computer Interface Understanding  Ontology (Real) Robot …… …..

  26. 과제 • AI 관련영화 보기 • 예) A.I 나 I. 로봇 • 가능한 다양한 관점으로 감상하여 평하기 • 공학적 • 인지과학적 • 윤리학적 • 철학적 ? • A4 1장 분량의 소감문 제출 • 보고서 표지 작성하지 마시고, 보고서 상단에 학번/이름 표기

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