Chapter1.ppt

1、Artificial Intelligence,Liu Lijue(刘丽珏) E_mail:jade_,2,Why do we use bilingual way to learn this course?,3,ARTIFICIAL INTELLIGENCE,首批国家精品课程 全国优秀网络课程 全国双语教学示范课程 So we use bilingual way to learn this course Origin of the modern science English learning Requirement and encouragement coming from our gove

2、rnment. “人工智能”网址： ,4,The Text Books,Cai Zixing and Xu Guangyou. Artificial Intelligence: Principles and Applications (人工智能及其应用，第三版本科生用书). Beijing：Tsinghua University Press, 2003 . 获国家教育部科技进步一等奖,5,Reference Book,N.J.Nilsson. Artificial Intelligence, A New Synthesis. Morgan Kaufmann, 1998 Zi-xing Cai,

3、 Intelligent Control: Principles, Techniques and Applications. Singapore-New Jersey: World Scientific. 1997,6,Course overview,What is AI. Knowledge representation. Searching and reasoning. Computational intelligence Uncertain knowledge and reasoning. Machine learning. The emphasis of the course is o

4、n the fundamentals, and not on providing a mastery of specific commercially available software tools or programming environments,7,What is Artificial Intelligence,What is AI? Not an easy science to describe It has fuzzy borders with mathematics, computer science, philosophy, psychology, statistics,

5、physics, biology and other disciplines Quick answer: getting machines to do smart things,8,What is AI,Where did Artificial Intelligence originate? AI is not “owned” by computer science Origins in (at least): maths, logic, computer science,philosophy, psychology, cognitive science, biology Understand

6、ing intelligence one of the oldest questions Turing introduced AI notions in his seminal work “AI” coined by John McCarthy in Dartmouth, 1956,9,What is AI,But what is “intelligence”? Intelligence is the computational part of the ability to achieve goals in the world. Varying kinds and degrees of int

7、elligence occur in people, many animals and some machines. (John McCarthy ) Simple things turn out to be the hardest to automate: Recognising a face. Navigating a busy street. Understanding what someone says. All tasks require reasoning on knowledge.,10,What is AI,Creative extension of philosophy Hi

8、ghly interdisciplinary Philosophy Mathematics Economics Neuroscience Psychology Computer Control theory Linguistics,11,What is AIDefinition,AI (Ability，能力): The ability of a machine (device) to perform functions that are normally associated with human intelligence, such as reasoning, planning, recog

9、nition, perception, cognition, learning, understanding, and problem-solving. AI (Discipline，学科): A branch of the computer science that deals with the research, design and application of the intelligent computer. Its major objective is to develop and use a machine to imitate some intellectual capabil

10、ities of human brain and to develop the related theories and techniques.,12,What Is AI? Definition,Intelligent Machine（智能机器） A kind of machine that can performs various anthropomorphic(类人的) tasks in an environment by learning autonomously or interactively. Intelligent System（智能系统） A system that can

11、drive (operate) intelligent machine to reach its goal. Intelligent Science（智能科学） A discipline that studies the essences of the human-being intelligent behavior, simulates the intelligence of human and living beings, and realizes various intelligent systems.,13,What is AI,Theres not an universally ac

12、cepted definition yet Various definitions Understand and build intelligent entities Getting computers to do tasks which require human intelligence It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using co

13、mputers to understand human intelligence.(John Mccarthy) AI is a field of study that encompasses computational techniques for performing tasks that apparently require intelligence when performed by humans,14,What is AI,Various definitions AI is the field of study that seeks to explain and emulate in

14、telligent behaviour in terms of computational processes AI is about generating representations and procedures that automatically or autonomously solve problems heretofore solved by humans AI is the part of computer science concerned with designing intelligent computer systems, that is, computer syst

15、ems that exhibit the characteristics we associate with intelligence in human behaviour - understanding language, learning, reasoning and solving problems Currently consist of huge variety of subfields This course will discuss some of them,15,What is AI,Different definitions due to different criteria

16、 Two dimensions: Thought processes/reasoning vs. behavior/action Success according to human standards vs. success according to an ideal concept of intelligence: rationality.,16,Systems that act like humans,Problem : not reproducible, constructive or amenable to mathematical analysis.(不可再现、无法构建、也不能用数

17、学分析来检验),17,Systems that think like humans,How do humans think? Requires scientific theories of internal brain activities (cognitive model): Level of abstraction? (knowledge or circuitry?) Validation? Predicting and testing human behavior Identification from neurological(神经学) data Cognitive Science v

18、s. Cognitive neuroscience. Both approaches are now distinct from AI Share that the available theories do not explain anything resembling human intelligence.,18,Systems that think rationally,Capturing the laws of thought Aristotle: What are correct argument and thought processes? Correctness depends

19、on irrefutability(不可反驳性) of reasoning processes. This study initiated the field of logic. The logicist tradition in AI hopes to create intelligent systems using logic programming. Problems: Not all intelligence is mediated by logic behavior What is the purpose of thinking? What thought should one ha

20、ve?,19,Systems that act rationally,Rational behavior: “doing the right thing” The “Right thing” is that what is expected to maximize goal achievement given the available information. Can include thinking, yet in service of rational action. Action without thinking: e.g. reflexes(条件反射). Two advantages

21、 over previous approaches: More general than law of thoughts approach More amenable to scientific development. Yet rationality is only applicable in ideal environments. Moreover rationality is not a very good model of reality.,20,Why do AI?,To accomplish tasks which, if we did them by hand would be

22、error prone This reliability may be very useful if the task is beyond some cognitive limitation of the brain, or when human intuition is counter-constructive To enable us to do things we couldnt do before Understand human intelligence in society,21,The Monty Hall Problem,Imagine youre on a TV game s

23、how called Lets Make a Deal, hosted by Monty Hall. Youre shown three doors and Monty says: Behind one is the big cash prize, behind the others is nothing. Please choose a door. After you choose a door, Monty says Now I know where that prize is., and he opens a door, behind which there is nothing. Mo

24、nty does this every week (hes very dramatic). This leaves only two doors shut, the one you chose and another one. Finally Monty asks: OK, do you want to change your mind and choose the other door? Should you?,22,The Monty Hall Problem,Q:Would an AI program, sufficiently programmed with probability t

25、heory and given a correct specification of the problem get the answer wrong? .tw/StatDemo/ConditionalProbability/ConditionalProbability.html,23,Why do AI?,Two general goals of AI（一般目标）: To understand human intelligence better. We test theories of human intelligence by writing

26、 programs which emulate it. To create useful “smart” programs able to do tasks that would normally require a human expert. Research Objectives Recent objective is to build intelligent computer to substitute some mental activities of human being. Further objective is to imitate the humans thinking lo

27、comotion(思维运动) and intellectual function using automata(自动机).,24,Who does AI?,Many disciplines contribute to goal of creating/modelling intelligent entities: Computer Science Psychology (human reasoning) Philosophy (nature of belief, rationality, etc) Linguistics (structure and meaning of language)

28、Human Biology (how brain works) Subject draws on ideas from each discipline.,25,Approaches to AI,AI researchers categorized as either weak or strong The strong AI people think that computers can achieve consciousness(意识) The weak AI people dont go that far Big AI and Small AI Big AI is the attempt t

29、o build robots of intelligence equaling that of humans Small AI is all about getting programs to work for small problems and trying to generalize the techniques to work on larger problems,26,Approaches to AI,The several paradigms can be clustered into three schools Symbolicism Connectionism Actionis

30、m Basic Technique of AI Knowledge representation Searching backpropagation. AI becomes a science (1987 - present) The emergence of intelligent agents (1995 - present) The whole agent problem: “How does an agent act/behave embedded in real environments with continuous sensory inputs” Recent 10 years,

31、 Computational Intelligence such as evolutionary computation, artificial life and immune computation,41,Human Intelligence and AI,Hypotheses of Intelligent Information Processing Systems (Physical Symbol System, Symbol Operation System ) 智能信息处理系统假设 Six basic functions: Input; Output; Store; Copy; Co

32、nstruct symbol structure; Conditional transfer The human can be viewed as an intelligent information processing system Hypothesis of Physical Symbol System: Six basic functions Intelligence,42,Human Intelligence and AI,Deductions（推论） Human have intelligence Human is an intelligent information proces

33、sing system Computer is an intelligent information processing system Computer can have intelligence Both of human and computer are intelligent information processing system We can use computer to simulate the human activities AI Can Simulate Human Intelligence（结论）,43,A Broad View of AI,Problem Solvi

34、ng 问题求解 IBM Deep Blue vs Garry Kasparov in 1997 & 2003 Logic Reasoning & Automatic Theorem Proving 逻辑推理与自动定理证明 Prove theorem by operating the fact data-base Natural deduction Theorem proving Computer-Aided proving,44,A Broad View of AI,Natural Language Understanding: 自然语言理解 deals with voice understa

35、nding and language translation do voice analysis, semantics understanding and syntax structure make frequency-spectrum(频谱) analysis and recognition establish knowledge base of specialized knowledge and common knowledge as well as the context,45,A Broad View of AI,Automatic Programming: 自动编程 related

36、to automatic theorem-proving and robotics mobile robots working in space, underwater or on land - sense and adapt the environment - execute the assigned tasks - to design the most suitable program automatically. Program synthesis: description - produce a program automatically to satisfy the requirem

37、ent of the task. Program verify: “old” program - “new” program.,46,A Broad View of AI,Machine Learning 机器学习 Based on large quantity of knowledge and knowledge base system. New branch- Data Mining & Knowledge Discover Expert System (ES) 专家系统 ES is an important and most active application area of AI.

38、ES is an intelligent computer programming system in which there exists knowledge and experience of specialized area in quantity in expert level, and can use the expert knowledge to handle and solve the problem in the specified domain. ES can be used to medicine, industry, agriculture, business ,educ

39、ation, entertainment and military,47,A Broad View of AI,Artificial Neural Network (ANN) 人工神经网络 ANN has been applied into the Pattern Recognition, Image Processing, Automation Control, Information Processing, Robotics and other AI areas. Robotics 机器人学 The AI & Robotics promote each other. The develop

40、ment of Intelligent Robots needs the guidance of the principles and techniques of AI, and Robotics can provide AI a suitable test-bed.,48,49,Robotics,50,A Broad View of AI,Pattern Recognition 模式识别 Pattern Recognition is to recognize the imitate sample of a given object. The “pattern” can be an objec

41、t, a graph, a voice, a character and/or light signal ect.,A Pattern Recognition Process,51,A Broad View of AI,Computer Vision : 计算机视觉 Image processing - Image understanding - machine vision real-time parallel processing active and qualitative vision dynamic and time-varying vision modeling & recognition of 3-dimension scenes compression, transmission and retrieval of real-time images processing and explanation of multi-spectr