Artificial Intelligence : An Introduction for CS570 Artificial Intelligence

1. Artificial Intelligence : An Introduction for CS570 Artificial Intelligence Jin Hyung Kim KAIST Computer Science Dept.

2. Definition of AI • Automation of activities that we associate with human thinking, activities such as decision-making, problem solving, learning, … (Bellman, 1978) • Study of how to make computers do things at which, at the moment, people are better (Rich & Knight, 1991) • A Branch of Computer Science that is concerned with the automation of intelligent behavior (Luger & Stubblefield, 1993) • The study of mental faculties through the use of computational models (Charniak & McDormott, 1995)

3. Computer Science Body of Knowledge 31 43 16 10 10 38 Total 280 Core Hours 3 8 21 31 15 18 36 Source : IEEE/ACM Computing Curricula 2001 Computer Science

4. Computing Disciplines,before and after 1990s

5. AI : Engineering Definition • Study of how to make machine do things which require intelligence when human do • things requiring intelligence ? • Making computer MORE smart • Making thinking computer • Can machine think ? • Focus on how good it performs

6. AI : Cognitive Scientific Definition • Studying intelligence by computational means • Programmed Human intelligence • Artificial Mind • Focus on how similar it works as human

7. Intelligent System Perception, Recognition, Understanding Making decisions, Acting Flexibility Automation Optimization Aims via

8. Examples of AI systems • Language Translation systems • Natural Language Question answering systems • Diagnosis Expert systems • Avionic Expert systems vs. fly-by-wire • Space shuttle mission planning • Robots in factory, Auto-navigation robots • Intelligent Traffic control system • OCR, Handwriting Recognition System • Speech Recognition System • …

9. Categorization of AI definitions

10. Go Playing Programs • Selecting next move • By analysis of all alternative moves • By Analysis of Board Pattern (rule-based) • Which one is better ? • Which one can be better ? • Engineering (mathematical) How well does it perform ? Performance is the key concern. Don’t care of what method used • Cognitive Scientific How similarly does it do as human ? Simulation of Behavior

11. Acting Humanly : Turing Test • Turing (1950) “Computing Machinery and Intelligence” • Can machine think ?  Can machine behave intelligently ? • Operational test of intelligent behavior : imitation game • Predicted that by 2000, a machine might have 30% chance of fooling a lay person in 5 minutes

12. Imitation Game

13. Issues on Turing Test • Intelligent as much as Human • Is dog intelligent ? • Searle’s Chinese Room argument • Strong AI and Weak AI • “ELIZA - a friend you could never have before” • http://www-ai.ijs.si/eliza-cgi-bin/eliza_script • Imitation of Client-centered Rogerian Therapy • Suggested major component of AI : knowledge, reasoning, language, understanding, learning • Any man-made system passed Turing Test ?

14. Thinking Rationally : Laws of Thought • Normative (or prescriptive ) rather than descriptive • Several school of Greek schools developed various forms of logic, notation and rules of derivation of thoughts • Mathematics and Philosophies of modern AI • Problems • Not all intelligent behavior is mediated by logical deliberation • What is purpose of thinking ? What thought should I have ? • Rational Behavior : doing the right thing • “right” – expected to maximize goal achievement given available information

15. Hype Cycle (Boom-Bust-Build) Science Fiction Hangover Productivity Curiosity

16. The Hype Cycle of Emerging Technologies ※자료 : Gartner, 2002 ※자료 : Gartner, 2002

17. Approaches to Intelligent system development u Knowledge-based Approach u Data Driven Approach u

18. Knowledge-base Systems u Represent Human knowledge as symbol combination u Knowledge Acquisition and Representation u Logic, Expert System, Fuzzy Logic u

19. Data Driven Approach u Extract common characteristics from collected examples u Training u Statistical Methods, Artificial Neural Network

20. Generality vs Power • Aims Powerful and general solutions • General Problem Solver • Early attempt : failed • Complexity : Toy Problems Only • Specialized Approach to get Power • Knowledge Based Approach • “Practical” Expert Systems

21. State of the Art • Which of the following can be done at present ? • Play a decent game of table tennis • Drive along a curvy mountain road • Drive in the center of Seoul city • Play decent game of Go • Discover and prove a new mathematical theorem • Write an intentionally funny story • Give competent legal advice in a specialized area of law • Translate spoken Korean into spoken Japanese in real time

22. Axes of AI Research Theory Methodology System Application

23. Major research areas (Methodology) • Symbolic Programming • Knowledge Representation • Search & Planning • Automated Reasoning • Machine Learning, knowledge Discovery • Artificial Neural Net • Genetic Algorithm • …...

24. Major research areas (Applications) • Natural Language Understanding • Image, Speech and pattern recognition • Uncertainty Modeling • Expert systems • Virtual Reality • …..

25. Symbolic Programming • Program as Representation of world • Symbol as basic element of representation • atom, property, relationship • Symbolic Expression as method of combination • LISP for Symbolic programming • PROLOG for logic programming • Object-Oriented Concept

26. Knowledge Representation • What kind of Knowledge needed for Problem solving ? • Structure of knowledge ? • declarative vs procedural • Representation techniques ? • explicit vs (implicit + inference) • logic, frame, object-oriented, semantic net, script • Knowledge acquisition and update

27. Search Theory • An Optimization method • Analyze alternative cases and select one • Cope with Exponential complexity, NP classes • Try likely one first (Heuristic Search) • Utilize local information (Hill Climbing Method) • Optimal solution vs good solution • Genetic Algorithm, Simulated Annealing • Stochastic search

28. Automated Reasoning • Qualitative Reasoning • Utilization of qualitative knowledge such as • Non-monotonic Reasoning • Ostrich flys ? • Plausible Reasoning • Information fusion under uncertainty • Case-based Reasoning • Utilization of Experience

29. Machine Learning • Performance improvement by experience • How much of knowledge required to start learning ? • Method of acquiring new knowledge and merging it to existing knowledge-base • Role of teacher • Role of examples and experience • Parameter Adjustment • Inductive learning • Computational Learning Theory • Quality of generalization capability in terms of Training data • Used in Practice such as Data Mining

30. Data Mining Knowlegre extraction for decision making Data Decision Making Information / knowledge • 인구통계 • Point of Sale • ATM • 금융통계 • 신용정보 • 문헌 • 첩보자료 • 진료기록 • 신체검사기록 • A상품 구매자의 80%가 B상품도 구매한다 • 미국시장의 자동차 구매력이 6개월간 감소 • A상품의 매출 증가가 B상품의 2배 • 탈수 증상을 보이면 위험 • 광고전략은 ? • 상품의 진열 • 최적의 예산 할당은 ? • 시장점유의 확대방안은 ? • 고객의 이탈 방지책은 ? • 처방은 ?

31. Neural Network • Computational model of Neurons • Power comes from Connection of simple processing element - connectionism X1 w1 w2 X2 F(X1, X2, …, Xn) S . . . wn Xn

32. Neural Network • learning = link weigh adjustment • Error-back-propagation : supervised learning • Any Functional Mapping is learnable • Strong at Sensory Data Processing • Symbolic Grounding • Old Horse on the race again • Massive parallelism, graceful degradation

33. Job(1/0) good age medium Salary bad #mouth Debt Neural Network Classifier Input layer Hidden layer Output layer

34. Genetic Algorithm • Computational model of life evolution • Stochastic optimization technique • Initial chromosome creation • New generations are made (cross over, mutation) • survival of the fittest • Base of artificial life research • study evolution of life, by simulation

35. History of AI • 50 years of rise and fall of New technologies after invention of computer • Logic • Optimization • Proabilistic Modeling • Search theory • Rule-based system • Expert systems • Fuzzy Theory • Neural Netwrok • Genetic Algorithm • Chaos theory • Artificial life • .....

36. AI Prehistory • Philosophy • Logic, methods of reasoning, mind as physical system, foundations of learning, language, rationality • Mathematics • Formal representation of proof, algorithms, computation, decidability, tractability, probability • Psychology • Adaption, phenomena of perception and motor control, experimental techniques • Linguistics • Knowledge representation, grammar • Neurosicence : Physical substrate for mental activity • Control Theory : homeostatic systems, stability, optimal designs

37. Potted History of AI (I) • 1943 : McCulloch & Pitts : Boolean Circuit model of Brain • 1950 : Turing’s “Computing Machinery and Intelligence” • 1950s : Early AI programs – Samuel’s checker program, Newell & Simon’s Logic Theorist • 1956 : Dartmouth meeting “Artificial Intelligence” adopted • 1965 : Robinson’s algorithm for logical reasoning

38. Potted History of AI (II) • 1966-74 : AI discovers computational complexity • 1969-79 : Early development of knowledge-based systems • 1980-88 : Expert systems industry booms, AI Programming Machine • 1983 – 1993 : Japan initiated 5th generation computer project • 1988-93 : Expert systems industry burst : “AI Winter” • 1985-95 : Neural Network back to the race • 1988 : Resurgence of probabilistic and decision-theoretic methods, Rapid increase of technical depth of mainstrean AI “Nouville AI : Alife, Genetic Algorithm, Soft computing

39. AI Success Story • Evans ANOLOGY • Symbolic Algebra • Macsyma (http://www.macsyma.com/) • Chess Program DEEP BLUE defeat Gary Kasparov (1996) • Automatic Theorem Proving contest (1999)

40. AI Success Story (Planning) • MARVEL (Schwuttke, 1992) • Real-time Space shuttle Mission planning • Berth assignment (KAL, 1997) • Unmanned Vehicle • Ground and air • Pathfinder Rover, 1996 • Asimo – a walking robot

41. Autonomous Land Vehicle(DARPA’s GrandChallenge contest)

42. AI Success Story (Language Processing) • PEGASUS (Zue, 1994) • Spoken Natural language for airline reservation • Limited context, free representation • Japanese-Korea Hotel reservation(KT, 1995) • Chatter Bot • 자연언어로 대화 (typing)하는 회사소개 에이젼트 등 • Many machine translation • 일한 실용화 완료, 영한 - 시제품

43. AI Success Story : Medical expert systems Programs listed by Special Field • Antibiotics & InfectiousDiseases • Cancer • Chest pain • Dentistry • Dermatology • Drugs & Toxicology • Emergency • Epilepsy • Family Practice • Genetics • Geriatrics • Gynecology • Imaging Analysis • Internal Medicine • Intensive Care • Laboratory Systems • Orthopedics • Pediatrics • Pulmonology & Ventilation • Surgery & Post-Operative Care • Trauma Management

44. Pattern Recognition Applications • Handwriting and document recognition • forms, postal mail, historic documents • PDA pen recognition • Signature, biometrics (finger, face, iris, etc.) • Gesture, facial expression • As a Human computer intertraction • EEG, EKG, X-ray • Trafic monitoring, Remote Sensing • Smart Weapon – guided missile, target homing

45. Automatic Target Recognizer

46. Postal Address Recognition

47. 전자 펜으로 수식 입력 수식 인식 Handwriting Understanding

48. 次世代 PC : e-Book, Tablet PC, PDA, M-phone

49. Ubiquitous 전자교실

50. BioInformatics / Protein Structure Analysis