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CmSc310 Artificial Intelligence Introduction to Artificial Intelligence 1. What is AI A question that has always been prevalent in the field of computer science is whether a computer can think. Can a machine emulate a human and can it ever display human intelligence? If so, how can we create such a machine? Thus, beyond the calculations and the information processing that computers are expected to do, an enigmatic branch of computer science called artificial intelligence was born. Below is the definition given by the Online Dictionary of Computing: [Artificial intelligence is] the subfield of computer science concerned with the concepts and methods of symbolic inference by computer and symbolic knowledge representation for use in making inferences. AI can be seen as an attempt to model aspects of human thought on computers. It is also sometimes defined as trying to solve by computer any problem that a human can solve faster. The purpose of AI is often cited as an attempt to model human thought on computers, that is, to make machines exhibit behavioral and thinking patterns that are similar to humans. Some important questions: 1. How do we define human behavioral and thinking patterns? 2. How do we define a rational behavior? 3. What should be the difference between an ordinary program (say a sorting program) and an AI program? 4. What is the essence of intelligent behavior? Strong AI: to create "a robot which is autonomous, thinks for itself, makes its own decisions, can deliberate about its own thoughts, can learn and adapt to new situations and can communicate with humans through the use of language." The term was introduced by Searle related to the "Chinese room argument" http://www.iep.utm.edu/chineser/ Weak AI: To build a computer program that simulates a particular intelligent activity, e.g. playing chess 1 2. Intelligent agents Features Goal-motivated behavior Decision making Knowledge-based (guided) behavior Adaptive behavior Interaction and communication Physical activity Topics State space search Logical systems; reasoning patterns Knowledge representation Information Data Knowledge Machine learning Vision, Pattern recognition Natural Language Processing Robotics Specifics of AI problems Require both procedural and declarative knowledge Require reasoning abilities Require planning Require learning abilities AI Landscape AI paradigms: Symbolic AI Connectionist AI AI methods Knowledge representation Semantic networks Frames Production rules Reasoning Predicate logic Probabilistic reasoning, Modal logic Common sense reasoning – the CYC project State space search State space: Initial state Goal state, intermediate states. Task - find a path between the initial and the goal states AI problems Planning, Decision making Pattern recognition, Vision Machine learning 2 Intelligent Agents Expert Systems Games Robots Softbots 3. Foundations of AI Philosophy 428 BC : birth of Plato Aristotle (student of Plato) tried to formulate more precisely the laws governing the rational part of the mind. Developed a system of syllogisms, which in principle allows to mechanically generate conclusions, given initial premises.. The big philosophical question - relation between mind and matter Mathematics Logic became a mathematical subject when George Boole in 1847 introduces a formal language for making logical inferences. Psychology/ Cognitive psychology / Cognitive Science How do we learn things about the world? Concerned with knowledge acquiring and representation in the human mind Computer Engineering Hardware suitable for modeling thought processes Sequential processing - not adequate Parallel and distributed processing Connectionist models Linguistics/ Computational Linguistics/ Natural language processing Obvious feature of intelligent entities - language use. Understanding language requires understanding subject matter and context. 4. History of AI 1923 Karel Capek's play "R.U.R." (Rossum's Universal Robots) opens in London (1923). - First use of the word 'robot' in English. 1943 Warren McCulloch and Walter Pitts: (1943) First work generally recognized as AI 3 Proposed a model of connected artificial neurons, capable of computing any computable function, and capable of learning. Used 3000 vacuum tubes to simulate a network of 40 neurons. 1950 Turing Test: A. M. Turing Computing Machinery and Intelligence Mind 49: 433-460 http://www.abelard.org/turpap/turpap.php http://archive.computerhistory.org/projects/chess/related_materials/text/2-0%20and%2021.Computing_machinery_and_intelligence.turing/2-0%20and%2021.Computing_machinery_and_intelligence.turing-alan.mind-59.1950.062303001.pdf Isaac Asimov (http://www.asimovonline.com/ ) published his three laws of robotics 1956 Dartmouth workshop 1956. Alan Turing, John McCarthy, Marvin Minsky, Alan Newell Proposed the name ARTIFICIAL INTELLIGENCE Dartmouth proposal: http://www.aaai.org/ojs/index.php/aimagazine/article/view/1904/1802 Logic Theorist - a reasoning program to prove theorems. (Newell and Simon) 1958 LISP (McCarthy) the second oldest language in current use Solving problems in microworlds: e.g. the block world 1965 ELIZA by Joseph Weinzenbaum (MIT), an interactive program that carries on a dialogue in English on any topic http://www.parnasse.com/drwww.shtml http://www-ai.ijs.si/eliza/eliza.html Work on machine translation - unsuccessful. 1966 Ross Quillian (PhD dissertation, Carnegie Inst. of Technology; now CMU) demonstrated semantic nets. Negative report on machine translation kills much work in Natural Language Processing (NLP) for many years. Difficulties: Lack of knowledge about world. The scale problem. 1969-1979 Knowledge -based systems DENDRAL (Buchanan et al, 1969) - inferring molecular structure from the information provided by a mass spectrometer. 4 SHRDLU Terry Winograd - understanding natural language in the block world http://hci.stanford.edu/~winograd/shrdlu/ http://hci.stanford.edu/winograd/ 1975 Knowledge representation - frames. Marvin Minsky http://en.wikipedia.org/wiki/Marvin_Minsky http://web.media.mit.edu/~minsky/ 1980 R1 - first commercial ES – Drew McDermott 1982, configures orders for new computer systems. http://cs-www.cs.yale.edu/homes/dvm/ http://en.wikipedia.org/wiki/Drew_McDermott 1984 Douglas Lenat (http://en.wikipedia.org/wiki/Douglas_Lenat started the CYC project with the goal to create a comprehensive ontology and a knowledge base of everyday common sense knowledge. http://www.cyc.com/ 1981 Fifth generation project in Japan - a ten year plan to build intelligent computers running Prolog 1986 Return of neural networks Parallel distributed processing, connectionist models 1987 Marvin Minsky : The Society of Mind, a theoretical description of the mind as a collection of cooperating agents 1990’s Major advances in all areas of AI, with significant demonstrations in machine learning, intelligent tutoring, case-based reasoning, multi-agent planning, scheduling, uncertain reasoning, data mining, natural language understanding and translation, vision, virtual reality, games, and other topics. 2000’s Robotics – interactive robot pets, NASA robots, military applications, social robots. 5 Military application: http://www.youtube.com/watch?v=mpBG-nSRcrQ http://www.youtube.com/watch?v=nUQsRPJ1dYw Playing soccer: http://www.youtube.com/watch?v=XLKKbz2mNyo 6