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1、Introduction to AI,Russell and Norvig: Chapter 1 CMSC421 Fall 2005,What is AI?,Found on the Web ,AI is the simulation of intelligent human processes AI is the reproduction of the methods or results of human reasoning or intuition AI is the study of mental faculties through the use computational meth
2、ods Using computational models to simulate intelligent behavior Machines to emulate humans,Why AI?,Cognitive Science: As a way to understand how natural minds and mental phenomena work e.g., visual perception, memory, learning, language, etc. Philosophy: As a way to explore some basic and interestin
3、g (and important) philosophical questions e.g., the mind body problem, what is consciousness, etc. Engineering: To get machines to do a wider variety of useful things e.g., understand spoken natural language, recognize individual people in visual scenes, find the best travel plan for your vacation,
4、etc.,Weak vs. Strong AI,Weak AI: Machines can be made to behave as if they were intelligent Strong AI: Machines can have consciousness subject of fierce debate, usually among philosophers and nay-sayers, not so much among AI researchers! E.g. recent Red Herring article and responses http:/ Character
5、izations,Discipline that systematizes and automates intellectual tasks to create machines that:,Act Like Humans,AI is the art of creating machines that perform functions that require intelligence when performed by humans Methodology: Take an intellectual task at which people are better and make a co
6、mputer do it Turing test,Prove a theorem Play chess Plan a surgical operation Diagnose a disease Navigate in a building,Turing Test,Interrogator interacts with a computer and a person via a teletype. Computer passes the Turing test if interrogator cannot determine which is which. Loebner contest: Mo
7、dern version of Turing Test, held annually, with a $100,000 prize. http:/ Participants include a set of humans and a set of computers and a set of judges. Scoring: Rank from least human to most human. Highest median rank wins $2000. If better than a human, win $100,000. (Nobody yet),Chess,Name: Garr
8、y Kasparov Title: World Chess Champion Crime: Valued greed over common sense,Humans are still better at making up excuses., Jonathan Schaeffer,Perspective on Chess: Pro,“Saying Deep Blue doesnt really think about chess is like saying an airplane doesnt really fly because it doesnt flap its wings” Dr
9、ew McDermott, Jonathan Schaeffer,Perspective on Chess: Con,“Chess is the Drosophila of artificial intelligence. However, computer chess has developed much as genetics might have if the geneticists had concentrated their efforts starting in 1910 on breeding racing Drosophila. We would have some scien
10、ce, but mainly we would have very fast fruit flies.” John McCarthy, Jonathan Schaeffer,Think Like Humans,How the computer performs functions does matter Comparison of the traces of the reasoning steps Cognitive science testable theories of the workings of the human mind,Connection with Psychology Ge
11、neral Problem Solver (Newell and Simon) Neural networks Reinforcement learning,But: Role of physical body, senses, and evolution in human intelligence? Do we want to duplicate human imperfections?,Think/Act Rationally,Always make the best decision given what is available (knowledge, time, resources)
12、 Perfect knowledge, unlimited resources logical reasoning Imperfect knowledge, limited resources (limited) rationality,Connection to economics, operational research, and control theory But ignores role of consciousness, emotions, fear of dying on intelligence,AI Characterizations,Discipline that sys
13、tematizes and automates intellectual tasks to create machines that:,History of AI,Jean-Claude Latombe: I personally think that AI is (was?) a rebellion against some form of establishment telling us “Computers cannot perform certain tasks requiring intelligence”,Bits of History,1956: The name “Artifi
14、cial Intelligence” was coined by John McCarthy. (Would “computational rationality” have been better?) Early period (50s to late 60s): Basic principles and generality General problem solving Theorem proving Games Formal calculus,Bits of History,1969-1971: Shakey the robot (Fikes, Hart, Nilsson) Logic
15、-based planning (STRIPS) Motion planning (visibility graph) Inductive learning (PLANEX) Computer vision,Bits of History,Knowledge-is-Power period (late 60s to mid 80s): Focus on narrow tasks require expertise Encoding of expertise in rule form: If: the car has off-highway tires and 4-wheel drive and
16、 high ground clearance Then: the car can traverse difficult terrain (0.8) Knowledge engineering 5th generation computer project CYC system (Lenat),Bits of History,AI becomes an industry (80s present): Expert systems: Digital Equipment, Teknowledge, Intellicorp, Du Pont, oil industry, Lisp machines: LMI, Symbolics, Constraint programming: ILOG Robotics: Machine Intelligence Corpo
