Foundations of Artificial Intelligence

1 Foundations of Artificial IntelligenceAIMA Chapter 1 (after Russell and Norvig)AIMA Chapter 1 (after Russell and Norvig) 1 Outline Administration What is AI? the understanding and building of intelligent entitites Foundations A brief history The state of the artAIMA Chapter 1 (after Russell and Norvig) 2 What is AI? [The automation of] activities that weassociate with human thinking, activitiessuch as decision-making, problem solving,learning.. (Bellman, 1978) The study of mental faculties throughthe use of computational models (Charniak+McDermott, 1985) The study of how to make computers dothings at which, at the moment, peopleare better (Rich+Knight, 1991) The branch of computer science thatis concerned with the automation of in-telligent behavior (Luger+Stubblefield,1993)Views of AI fall into four categories:Thinking humanlyThinking rationallyActing humanlyActing rationallyExamining these, we will plump for acting rationally (sort of)AIMA Chapter 1 (after Russell and Norvig) 3 Acting humanly: The Turing testTuring (1950) Computing machinery and Intelligence : Can machines think?

2 Can machines behave intelligently? Operational test for intelligent behavior: the Imitation Game Predicted that by 2000, a machine might have a 30% chance offooling a lay person for 5 minutes Anticipated all major arguments against AI in following 50 years Suggested major components of AI: knowledge, reasoning, languageunderstanding, learningProblem: Turing test is not reproducible, constructive, oramenable to mathematical analysisLoebner Prize: The first formal instantiation of a Turing test Chapter 1 (after Russell and Norvig) 4 Thinking humanly: Cognitive Science1960s cognitive revolution : information-processing psychology replacedprevailing orthodoxy of behaviorismRequires scientific theories of internal activities of the brain What level of abstraction? Knowledge or circuits ? How to validate? Requires1) Predicting and testing behavior of human subjects (top-down)or 2) Direct identification from neurological data (bottom-up)Both approaches (roughly, Cognitive Science and CognitiveNeuroscience)are now distinct from AIBoth share with AI the following characteristic and thus direction:the avail-able theroeis do not explain (or engender) anything resembling human-level general intelligenceAIMA Chapter 1 (after Russell and Norvig) 5 Thinking rationally: Laws of ThoughtNormative(or prescriptive) rather than descriptiveAristotle: what are correct arguments/thought processes?

3 Several Greek schools developed various forms of logic:notationand rules of derivationfor thoughts;may or may not have proceeded to the idea of mechanizationDirect line through mathematics and philosophy to modern AIProblems:1) Not all intelligent behavior is mediated by logical deliberation2) What is the purpose of thinking? What thoughts should I have?3) Computationally intractable4) Expressive inadequaciesAIMA Chapter 1 (after Russell and Norvig) 6 Acting rationallyRationalbehavior: doing the right thingThe right thing: that which is expected to maximize goal achievement,given the available informationDoesn t necessarily involve thinking , blinking reflex butthinking should be in the service of rational actionAristotle (Nicomachean Ethics):Every art and every inquiry, and similarly every actionand pursuit, is thought to aim at some goodBeyond programs: autonomy, perception, persistence, adaptive, goal adop-tionAIMA Chapter 1 (after Russell and Norvig) 7 Rational agentsAn agentis an entity that perceives and actsAbstractly, an agent is a function from percept histories toactions:f:P AFor any given class of environments and tasks, we seek theagent (or class of agents) with the best performanceCaveat.

4 Computational limitations make perfect rationality unachievable design best programfor given machine resourcesAIMA Chapter 1 (after Russell and Norvig) 8 Course: Rational agentsThis course is about designing rational agentsThinking rationally is only one way of acting rationallyRationality is more clearly defined and general than human-centered ap-proachesAIMA Chapter 1 (after Russell and Norvig) 9AI Prehistory and HistoryMany disciplines (philosophy, mathematics, economics, psychology, linguis-tics, computer engineering, control theory, neuroscience, and more) havecontributed ideas, viewpoints, and techniques to AIThe history of AI has had cycles of success, misplaced optimism, and resultingretrenchments; cycles of new creativity and systematic refinement of bestapproachesAIMA Chapter 1 (after Russell and Norvig) 10 Potted history of AI1943-1955: Gestation1956: Birth1952-1969: Great Expectations1966-1973: Reality1969-1979: Knowledge is Power1980-present: AI and Industry1986-present: The Return of Neural Networks1987-present: AI Becomes a Science1995-present.

5 Intelligent AgentsAIMA Chapter 1 (after Russell and Norvig) 11AI becomes a science, Intelligent Agents1987 Rapid increase in technical depthBuild on existing theoriesBase claims on theorems and/or experments rather than intuitionReal world applications rather than toy examplesReplication of experiments with data and code repositoriesLess isolationism1995 Whole agents rather than fragmentsSituated movementInternet environments ( bots )AIMA Chapter 1 (after Russell and Norvig) 12 State of the artAutonomous planning and scheduling (NASA)Game playing (Deep Blue)Automomous control (minivan steering)Diagnosis (medicine)Logistics planning (Gulf war)Robotics (surgery)Language understanding and generation (translation, dialogue)Problem solving (crossword puzzles)AIMA Chapter 1 (after Russell and Norvig) 13 SummaryDifferent people think of AI differently (thinking or behavior, humans orideal)We will adopt the Rational Action view: an Intelligent Agenttakes the bestpossible action in a situationAI has its roots in many disciplinesThe history of AI has had various cyclesCurrently: greater use of the scientific method, progress inboth theory andpractice, integration within subfields and across disciplinesAIMA Chapter 1 (after Russell and Norvig) 14