CS 188: Artificial Intelligence Fall 2008AdministriviaCourse StaffCourse DetailsAnnouncementsTodaySci-Fi AI?What is AI?Acting Like Humans?Thinking Like Humans?Thinking Rationally?Acting RationallySlide 13Rational AgentsA (Short) History of AIWhat Can AI Do?Unintentionally Funny StoriesNatural LanguageVision (Perception)RoboticsLogicGame PlayingDecision MakingCourse TopicsCourse ProjectsCS 188: Artificial IntelligenceFall 2008Lecture 1: Introduction8/28/2008Dan Klein – UC BerkeleyMany slides over the course adapted fromeither Stuart Russell or Andrew MooreAdministriviahttp://inst.cs.berkeley.edu/~cs188Course StaffCourse StaffSlav PetrovDan KleinGSIsProfessorAria HaghighiAnh PhamPercy LiangAnna RaffertyAlex SimmaDavid GollandCourse DetailsBook: Russell & Norvig, AI: A Modern Approach, 2nd Ed.Prerequisites:(CS 61A or B) and (Math 55 or CS 70) There will be a lot of statistics and programmingWork and Grading:Four assignments divided into checkpointsProgramming: Python, groups of 1-2Written: solve together, write-up alone5 late daysMid-term and finalParticipationFixed scaleAcademic integrity policyAnnouncementsImportant stuff:Python lab: THIS Friday and Wednesday, 11am-4pm in 275 Soda HallGet your account forms (in front after class)First assignment on web soonSections this coming week; start out in your assigned section, but can then move if spaceWaitlist: I don’t control enrollment, but most should get inCommunication:Announcements: webpageNewsgroupStaff email: [email protected]IRC?Questions?TodayWhat is AI?Brief history of AIWhat can AI do?What is this course?Sci-Fi AI?What is AI?Think like humans Think rationallyAct like humans Act rationallyThe science of making machines that:Acting Like Humans?Turing (1950) “Computing machinery and intelligence”“Can machines think?” “Can machines behave intelligently?”Operational test for intelligent behavior: the Imitation GamePredicted by 2000, a 30% chance of fooling a lay person for 5 minutesAnticipated all major arguments against AI in following 50 yearsSuggested major components of AI: knowledge, reasoning, language understanding, learningProblem: Turing test is not reproducible or amenable to mathematical analysisThinking Like Humans?The cognitive science approach:1960s ``cognitive revolution'': information-processing psychology replaced prevailing orthodoxy of behaviorismScientific theories of internal activities of the brainWhat level of abstraction? “Knowledge'' or “circuits”?Cognitive science: Predicting and testing behavior of human subjects (top-down)Cognitive neuroscience: Direct identification from neurological data (bottom-up)Both approaches now distinct from AIBoth share with AI the following characteristic:The available theories do not explain (or engender) anything resembling human-level general intelligenceHence, all three fields share one principal direction!Images from Oxford fMRI centerThinking Rationally?The “Laws of Thought” approachWhat does it mean to “think rationally”?Normative / prescriptive rather than descriptiveLogicist tradition:Logic: notation and rules of derivation for thoughtsAristotle: what are correct arguments/thought processes?Direct line through mathematics, philosophy, to modern AIProblems:Not all intelligent behavior is mediated by logical deliberationWhat is the purpose of thinking? What thoughts should I (bother to) have?Logical systems tend to do the wrong thing in the presence of uncertaintyActing RationallyRational behavior: doing the “right thing”The right thing: that which is expected to maximize goal achievement, given the available informationDoesn't necessarily involve thinking, e.g., blinkingThinking can be in the service of rational actionEntirely dependent on goals!Irrational ≠ insane, irrationality is sub-optimal actionRational ≠ successfulOur focus here: rational agentsSystems which make the best possible decisions given goals, evidence, and constraintsIn the real world, usually lots of uncertainty… and lots of complexityUsually, we’re just approximating rationality“Computational rationality” a better title for this courseMaximize Your Expected UtilityRational AgentsAn agent is an entity thatperceives and acts (moreexamples later)This course is about designingrational agentsAbstractly, an agent is a functionfrom percept histories to actions:For any given class of environments and tasks, we seek the agent (or class of agents) with the best performanceComputational limitations make perfect rationality unachievableSo we want the best program for given machine resources[demo: pacman]A (Short) History of AI1940-1950: Early days1943: McCulloch & Pitts: Boolean circuit model of brain1950: Turing's “Computing Machinery and Intelligence”1950—70: Excitement: Look, Ma, no hands!1950s: Early AI programs, including Samuel's checkers program, Newell & Simon's Logic Theorist, Gelernter's Geometry Engine1956: Dartmouth meeting: “Artificial Intelligence” adopted1965: Robinson's complete algorithm for logical reasoning1970—88: Knowledge-based approaches1969—79: Early development of knowledge-based systems1980—88: Expert systems industry booms1988—93: Expert systems industry busts: “AI Winter”1988—: Statistical approachesResurgence of probability, focus on uncertaintyGeneral increase in technical depthAgents and learning systems… “AI Spring”?2000—: Where are we now?What Can AI Do?Quiz: Which of the following can be done at present?Play a decent game of table tennis?Drive safely along a curving mountain road?Drive safely along Telegraph Avenue?Buy a week's worth of groceries on the web?Buy a week's worth of groceries at Berkeley Bowl?Discover and prove a new mathematical theorem?Converse successfully with another person for an hour?Perform a complex surgical operation?Unload a dishwasher and put everything away?Translate spoken Chinese into spoken English in real time?Write an intentionally funny story?Unintentionally Funny StoriesOne day Joe Bear was hungry. He asked his friend Irving Bird where some honey was. Irving told him there was a beehive in the oak tree. Joe walked to the oak tree. He ate
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