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Introduction to Artificial Intelligence LECTURE 1: Introduction • • • • What is AI? Foundations of AI The History of AI State of the Art Introduction to AI, H. Feili ([email protected]) 1 Definitions of AI • Develop programs/systems that perform/act like humans • Develop programs/systems that peform/act rationally • Understand human intelligence • Formalize the laws of thought and action INTELLIGENT AGENTS Introduction to AI, H. Feili ([email protected]) 2 What is AI? The Turing Test HUMAN COMPUTER/ HUMAN - types in questions - receives answers on screen - processes questions - returns answers If the human cannot tell if it is a computer or a human, the program exhibits intelligence Introduction to AI, H. Feili ([email protected]) 3 Examples of task for AI • Play games – tic-tac-toe, chess, backgammon, poker • Process natural language – control tower conversation, stock market briefs • Industrial applications – plant diagnostics, plan for manufacturing • Expert-level performance – molecular biology, computer configuration Introduction to AI, H. Feili ([email protected]) 4 Why is AI different than conventional programming? • Strive for – GENERALITY – EXTENSIBILITY • Capture rational deduction patterns • Tackle problems with no algorithmic solution • Represent and manipulate KNOWLEDGE, rather than DATA • A new set of representation and programming techniques: HEURISTICS Introduction to AI, H. Feili ([email protected]) 5 Example: TIC-TAC-TOE Introduction to AI, H. Feili ([email protected]) 6 Program 1: hard wired • Code a table of all possible board positions and the transitions between them (state diagram) • Given a position, look in the table for the next move and return • Properties: – time efficient, requires lots of storage – not extensible: requires a table for other games Introduction to AI, H. Feili ([email protected]) 7 Program 2: less hard wired • Use procedures designed for the game: – try to place two marks in a row – if opponent has two marks in a row, place mark in third space • • • • Pattern matching to recognize board positions Can encode different playing strategies Better space efficiency, less time efficiency Still game-dependent Introduction to AI, H. Feili ([email protected]) 8 Program 3: AI-like • Represent the state of the game: – current board position – next legal positions • Use an evaluation function: – Rate the next move according to how likely it will lead to a win – look-ahead of possible oponent moves • More general because it embodies a general strategy. Introduction to AI, H. Feili ([email protected]) 9 Foundations of AI • Philosophy: Aristotle, mechanistic views, materialism, positivism, rationality. • Mathematics: algorithms, logic, formalization of mathematics, incompleteness, decision theory. • Psychology: behaviorism, cognitive science. • Linguistics: grammars, syntax and semantics. • Computer Science: computers, software, theory • Others: neuroscience, economics, game theory. Introduction to AI, H. Feili ([email protected]) 10 A brief history of AI (1) • Gestation (43-56): – automata theory, neural networks, checkers, theorem proving. – Shannon, Turing, Von Neumann, Newell and Simon, Minsky, McCarthy, Darmouth Workshop. • Great expectations (52-69): – computers can do more than arithmetics! – General Problem Solver (GPS), better checkers – LISP (LISt Processing language) Introduction to AI, H. Feili ([email protected]) 11 A brief history of AI (2) – Microworlds: ANALOGY, blocks world Introduction to AI, H. Feili ([email protected]) 12 A brief history of AI (3) • A dose of reality (66-74): – ELIZA: human-like conversation. – limitations of neural networks, genetic algorithms, machine evolution. – acting in the real world: robotics. • Knowledge-based systems (69-79): – domain focus: experts systems vs. General Problem Solvers. – DENDRAL, MYCIN, XCON, etc. Introduction to AI, H. Feili ([email protected]) 13 A brief history of AI (4) • Commercial AI: the ‘80s boom (80-90) – DEC’s R1 computer configuration program – many expert systems tools companies (mostly defunct): Symbolics, Teknowledge, etc. – Japan’s 5th generation project: PROLOG. – limited success in autonomous robotics and vision systems. Introduction to AI, H. Feili ([email protected]) 14 A brief history of AI (5) • The 90’s: specialization, quiet progress – – – – – – neural networks, genetic algorithms probabilistic reasoning and uncertainty learning planning and constraint solving agents autonomous robotics: NAV autonomous driving van, crater exploration, robot soccer – IBM’s Deep Blue beats Kasparov! Introduction to AI, H. Feili ([email protected]) 15 State of the Art • Embedded AI: many use AI techniques without saying it is AI! – Credit card approval (American Express) – Consumer electronics (fuzzy logic) • Healthy research in many areas: intelligent agents, machine learning, man-machine interfaces, etc. • More integrative view: acting in the real world (robots, self diagnosing machines) Introduction to AI, H. Feili ([email protected]) 16 To find out more about AI – “Godel, Escher, Bach” D. Hoftstadter – Annual AI conferences : American Assoc of Artificial Intelligence (AAAI) Int. Joint Conf. On Artificial Intelligence (IJCAI) – Specialized conferences: Machine Learning, Knowledge Representation, Vision, Robotics, etc. – A dozen journals: the main one is Artificial Intelligence Introduction to AI, H. Feili ([email protected]) 17 ? Introduction to AI, H. Feili ([email protected]) 18