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Introduction to Artificial Intelligence Introduction What is Artificial Intelligence? Notes It is a young area of science (1956) Its goals are what we consider Intelligent behaviour There are many approaches from different points of view It has received influence from very diverse areas (Philosophy, Mathematics, Psychology, Biology) Involves many areas of work with generic goals (learning, perception, problem solving . . .) and specific goals (chess, diagnosis of diseases, driving cars, ...) C \ BY: $ (LSI-FIB-UPC) Artificial Intelligence Introduction to Artificial Intelligence Term 2009/2010 1 / 20 Introduction A definition of Artificial Intelligence Notes Systems that act like humans Systems that think like humans “The study of how to make computers do things at which, at the moment, people are better” (Rich & Knight, 1991) “The exciting new effort to make computers think ... machines with minds, in the full and literal sense” (Haugeland, 1985) “Computational intelligence is the study of the design of intelligent agents” (Poole et al, 1998) “The study of mental faculties through the use of computational models” (Charniak & McDermott, 1985) Systems that act rationally Systems that think rationally C \ BY: $ (LSI-FIB-UPC) Artificial Intelligence Introduction to Artificial Intelligence Term 2009/2010 2 / 20 Introduction Systems that act like humans Notes The model is the human being, the goal is to build a system that can pass as human. Turing’s Test: If a system pass the test is intelligent (?) Abilities: Natural language processing, knowledge representation, reasoning, learning. It is not the goal of AI to pass the test The interaction between programs and people brings the necessity to make programs that act like humans. C \ BY: $ (LSI-FIB-UPC) Artificial Intelligence Term 2009/2010 3 / 20 Introduction to Artificial Intelligence Introduction Turing’s test C \ BY: $ (LSI-FIB-UPC) Notes Artificial Intelligence Introduction to Artificial Intelligence Term 2009/2010 4 / 20 Introduction Systems that think like humans Notes The model is how the human mind works By experimentation we obtain a theory about how the mind works (psychological experiments) From this theory we can build computational models Cognitive science C \ BY: $ (LSI-FIB-UPC) Artificial Intelligence Introduction to Artificial Intelligence Term 2009/2010 5 / 20 Introduction Systems that think rationally Notes The laws of rationality are based on logic Formal logic has to be the basis of intelligent systems (Logicism) There are two obstacles: It is very difficult to formalize knowledge in logic language There is a great leap between the theoretical capacity of logic and its practical application C \ BY: $ (LSI-FIB-UPC) Artificial Intelligence Term 2009/2010 6 / 20 Introduction to Artificial Intelligence Introduction Systems that act rationally Notes To act rationally means to perform acts to achieve the best outcome, to obtain some goals given some beliefs The paradigm is the agent An agent perceives and act, accordingly to the environment it is situated The capacities that are needed are the same than those to pass the Turing’s test: Natural language processing, knowledge representation, reasoning, learning, perception It is a more general approach, not centered on the human model C \ BY: $ (LSI-FIB-UPC) Artificial Intelligence Introduction to Artificial Intelligence Term 2009/2010 7 / 20 Introduction Is Artificial Intelligence possible? Notes The possibility to build an artificial intelligence raises some complex philosophical problems Are thinking machines conscious? The chinese room, (Searle, 1980) Is intelligence an emerging property of the biological elements that sustains it? There is no definitive conclusion C \ BY: $ (LSI-FIB-UPC) Artificial Intelligence Introduction to Artificial Intelligence Term 2009/2010 8 / 20 Introduction The chinese room C \ BY: $ (LSI-FIB-UPC) Notes + −> + −> + −> Artificial Intelligence Term 2009/2010 9 / 20 Introduction to Artificial Intelligence Foundations of Artificial Intelligence Foundations of Artificial Intelligence - Philosophy Notes Are mechanical intelligences possible? Aristotle Llull Decart Laws that govern the rational part Actions are justified by a connection bet- Knowledge = Logic Theories Aristotle C \ Perception is the source of knowledge (Induction) ween goals and knowledge BY: $ (LSI-FIB-UPC) Leibniz The mind is a physical system of the mind (logic) Russell Artificial Intelligence Introduction to Artificial Intelligence Hume Bacon Term 2009/2010 10 / 20 Foundations of Artificial Intelligence Foundations of Artificial Intelligence - Mathematics Notes Mathematics Logic Boole Complexity Frege What are the rules of reasoning? C \ BY: $ (LSI-FIB-UPC) Gödel Turing What is computable? Probability Fermat Bernoulli Bayes How to reason with uncertainty? Artificial Intelligence Introduction to Artificial Intelligence Term 2009/2010 11 / 20 Foundations of Artificial Intelligence Foundations of Artificial Intelligence (III) Notes Economics ¿How do we make decisions ... that benefit us? against competitors? when there is not immediate benefit? Decision theory/Game theory/Operations research Neuroscience How does the brain process information? Neurons/Specialized areas in the brain Psychology How does people act and think? Cognitive psychology/Cognitive science: Behavioural theories, foundations of rational behaviour C \ BY: $ (LSI-FIB-UPC) Artificial Intelligence Term 2009/2010 12 / 20 Introduction to Artificial Intelligence Foundations of Artificial Intelligence Foundations of Artificial Intelligence (IV) Notes Computer Science In order AI to exist it is needed a physical device to support it (Hardware) AI needs also software tools to develop intelligent systems Control theory/Cybernetics Development of autonomous systems Linguistics Chomsky: Knowledge representation, language grammar Computational linguistics C \ BY: $ (LSI-FIB-UPC) Artificial Intelligence Term 2009/2010 13 / 20 Areas of Artificial Intelligence Areas of Artificial Intelligence Notes Basic areas Knowledge representation Automatic problem solving, heuristic search Specific areas Automatic planning Natural language processing Automatic reasoning Knowledge based systems Perception Machine learning Intelligent agents C \ BY: $ (LSI-FIB-UPC) Artificial Intelligence Areas of Artificial Intelligence Term 2009/2010 14 / 20 Applications of Artificial Intelligence Autonomous robots Notes Autonomous Navigation Assistive Technologies Complex tasks (vision, planning, coordination, real time, ...) C \ BY: $ (LSI-FIB-UPC) Artificial Intelligence Term 2009/2010 15 / 20 Areas of Artificial Intelligence Applications of Artificial Intelligence Image recognition Faces Medical Images Hand writing recognition Object recognition BY: $ (LSI-FIB-UPC) C \ Notes Artificial Intelligence Areas of Artificial Intelligence Term 2009/2010 16 / 20 Applications of Artificial Intelligence Computer games Notes Path finding Strategy Coordination, cooperation, learning, adaptation, ... C \ BY: $ (LSI-FIB-UPC) Artificial Intelligence Areas of Artificial Intelligence Term 2009/2010 17 / 20 Applications of Artificial Intelligence Electronics appliances Intelligent vacuum cleaners Notes Cameras with face recognition Apliances with intelligent control C \ BY: $ (LSI-FIB-UPC) Artificial Intelligence Term 2009/2010 18 / 20 Areas of Artificial Intelligence Applications of Artificial Intelligence Intelligent Interfaces/Recommendation/Personalization Ambient Intelligence C \ BY: $ (LSI-FIB-UPC) Notes Recommendation/Personalization Artificial Intelligence Areas of Artificial Intelligence Term 2009/2010 19 / 20 Applications of Artificial Intelligence Diagnostic/Control/Design/Planning systems Notes Medicine Logistics Intelligent Manufacturing Industrials Processes Industrial Design Complex Processes (LSI-FIB-UPC) \ $ C BY: Artificial Intelligence Term 2009/2010 20 / 20 Notes