Lecture 1 Course webpage http://csserver.evansville.edu/~hwang/s12-courses/cs430.html Handouts, assignments Syllabus and schedule, textbook Access to a Scheme system, recommend Racket (formerly PLT Scheme and before that DrScheme). Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 1 Outline What is AI? Foundations of AI History of AI State of the Art Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 2 What is AI? Done Like a Human Done Rationally Thinking Think Like a Human Think Rationally Acting Act Like a Human Act Rationally Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 3 Act Like a Human Turing Test Approach "The art of creating machines that perform functions that require machine intelligence when performed by people." (Kurzweil, 1990) "The study of how to make computers do things at which, at the moment, people are better." (Rich and Knight, 1991) What would it take for a computer to act like a human? Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 4 Think Like a Human Cognitive Modeling Approach "The exciting new effort to make computers think ... machines with minds, in the full and literal sense." (Haugeland, 1985) "[ The automation of ] activities that we associate with human thinking, activities such as decision-making, problem solving, learning..." (Bellman, 1978) Does it matter whether the computer uses the same reasoning as a human to solve a problem? Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 5 Think Rationally "Laws of Thought" Approach "The study of mental faculties through the use of computational models" (Charniak and McDermott, 1985) "The study of the computations that make it possible to perceive, reason, and act." (Winston, 1992) How is informal knowledge like common sense represented formally in logic? Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 6 Act Rationally "Computational Intelligence is the study of the design of intelligent agents." (Poole, et al., 1998) "AI ... is concerned with intelligent behavior in artifacts." (Nilsson, 1998) Is it possible to always determine "the right thing" to do? Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 7 Foundations of AI Philosophy – methods of reasoning Mathematics – formalization Economics – systems for maximizing payoff Neuroscience – how does human brain process information Psychology – how do humans think and act Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 8 Foundations of AI Computer engineering – how to build an efficient computer Control theory & Cybernetics – how can machines operate under their own control Linguistics – how is language related to thought Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 9 History of AI 1943-1955, pre-AI work in artificial neural networks, introduction of the Turing Test (1950) summer of 1956, birth of AI at Dartmouth Conference led by John McCarthy, Newell & Simon Logic Theorist program 1952-1969, early success refuting "a machine will never be able to do X" in limited problem domains, invention of Lisp & time-sharing, lots of predictions of success in near future Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 10 History of AI 1966-1973, back to reality, instead of 10 years to success for complex problems more like 40 years, need to know something about complex problem domains, need more computing power 1969-1979, success with knowledge-based (expert) systems, knowledge representation 1980-present, AI becomes an industry, AI expert systems save millions of dollars, Japanese "Fifth Generation" project Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 11 History of AI 1986-present: neural networks return, work in effective computationl architectures and effective modeling 1987-present: incorporate scientific method, claims based on rigorous theorems or experimental evidence, hidden Markov models, Bayesian networks 1995-present: intelligent agents, especially on the Internet ('bots) 2001-present: large data sets Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 12 State of the Art Robotic vehicles: 2005 DARPA Grand Challenge, 2006 DARPA Urban Challenge Speech recognition: United Airlines reservation system Autonomous planning and scheduling: NASA Remote Agent, MAPGEN (Mars Rovers), European Space Agency MEXAR2 (Mars Express) Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 13 State of the Art Game playing: IBM Deep Blue defeated world chess champion Garry Kasparov in 1997 Spam detection: learning algorithms filter the 80-90% of email that is junk Logistics planning: 1991 Persian Gulf War DART generated plans in hours that would have taken weeks. DARPA stated this more than paid back its 30-year investment in AI Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 14 State of the Art Robotics: iRobot Roomba vacuum cleaners, Packbots in Iraq & Afghanistan Machine translation: credible Arabic to English translator Tuesday, January 10 CS 430 Artificial Intelligence - Lecture 1 15