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Course: Engineering Artificial Intelligence Dr. Radu Marinescu Cork Constraint Computation Centre (4C) University College Cork University College Cork (Ireland) Department of Civil and Environmental Engineering CE6017 o Course homepage • http://4c.ucc.ie/~rmarines/teaching.html • and the UCC Blackboard o Lectures • Tuesdays 17:30 – 19:00 + tutorial 19:30 – 20:30 • 2 blocks 13 & 14 November • Final project (80%) • Homework (20%) o Instructor • Dr. Radu Marinescu (email: [email protected]) • Office hours (by appointment): Monday 18:00 – 19:00 location: Western Gateway Building (on Western Rd.), Room 2-70 University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 2 Course resources o Textbook • “Artificial Intelligence – A Modern Approach” 2nd edition by Stuart Russell and Peter Norvig. Prentice Hall Series in Artificial Intelligence, 2003 o Resources on the Web • AI on the Web: A very comprehensive list of Web resources about AI from the RN textbook (http://aima.cs.berkeley.edu/ai.html) o Essays • What is AI?, John McCarthy • Computing Machinery and Intelligence, Alan Turing • Rethinking Artificial Intelligence, Patrick H. Winston University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 3 Course overview Introduction o Intelligent agents o Search o Constraint processing o Representation and reasoning with logic o Learning o o Uncertainty University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 4 Today’s class What is Artificial Intelligence? o Intelligent agents o A brief history o o State-of-the-art AI systems University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 5 What is Artificial Intelligence? o Could you please give your definition? • For me, AI is … • AI may be defined as … University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 6 What is Artificial Intelligence? o What is artificial intelligence? • It is the science and engineering of making intelligent machines, especially intelligent computer programs. • It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable. o Yes, but what is intelligence? • Intelligence is the computational part of the ability to achieve goals in the world. Varying kinds and degrees of intelligence occur in people, animals and some machines. University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 7 What is Artificial Intelligence? o Isn't there a solid definition of intelligence that doesn't depend on relating it to human intelligence? • Not yet. The problem is that we cannot yet characterize in general what kinds of computational procedures we want to call intelligent. We understand some of the mechanisms of intelligence and not others. o More in: • http://www-formal.stanford.edu/jmc/whatisai/node1.html University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 8 What is Artificial Intelligence? o “The science of making machines do things that would require intelligence if done by humans” Marvin Minsky University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 9 Artificial Intelligence o Although AI has a strong science fiction connotation, it forms a vital branch of computer science, dealing with intelligent behavior, learning and adaptation in machines University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 10 What is Artificial Intelligence? o Views on AI fall into four categories: Think humanly Think rationally Acting humanly Acting rationally o Human-centered approach • Must be an empirical science, involving hypothesis and experimental confirmation o Rationalist approach • Involves a combination of mathematics and engineering University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 11 Acting Humanly - The Turing test o Can machines think? • The computer passes the test if a human interrogator, after posing some written questions, cannot tell if whether the written responses come from a person or not (Alan Turing, 1950) o Requires • Natural language processing • Knowledge representation • Automated reasoning • Machine learning • Vision and robotics (to pass the full test) These six disciplines compose most of AI University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 12 Thinking Humanly o o If we’re going to say that a program thinks like a human, we must have a way of determining how humans think (we need to get inside the actual working of the human mind) If the program’s input/output and timing behaviors match corresponding human behavior, that is evidence that some of the program’s mechanisms could also be operating in humans • GPS (General Problem Solver) by Allen Newell and Herbert Simon – the author were not interested to see if the program solves the problems correctly, but rather they were interested to compare the trace of its reasoning steps to traces of human subjects solving the same problems University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 13 Thinking Rationally – the “laws of thought” approach o o So-called logicist approach within artificial intelligence hopes to build programs that, in principle, could solve any solvable problem described in logical notation Problems • It is not easy to take informal knowledge and state it in the formal terms required by logical notation, particularly when the knowledge is not 100% certain • There is a big difference between being able to solve a problem “in principle” and doing so in practice. Even problems with a few dozen facts can exhaust the computational resources of a modern computer, unless it has some guidance as to which reasoning steps to apply first University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 14 Acting Rationally – the rational agent approach o A rational agent is one that acts so as to achieve the best possible outcome or, when there is uncertainty, the best expected outcome • Operating under autonomous control, perceiving its environment, persisting over prolonged period of time, adapting to change, and being able of taking on another’s goals o Rational-agent design • More general than “think rationally” (logical) approach, because correct inference is just one of several mechanisms for achieving rationality • Amendable to scientific development than human-centered approaches because human behavior or human thought are not fully understood University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 15 Research in AI o Research in AI is concerned with producing machines to automate tasks requiring intelligent behavior • It is a scientific discipline, focused on providing solutions to real life problems • AI systems are now in routine use: economics, medicine, engineering, military, as well as home computer software applications and video games (see examples later) University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 16 Research in AI o Major subfields • Control • Planning • Vision • Robotics • Natural Language Processing • Speech Processing • Automated Reasoning (probabilistic, deterministic) University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 17 History of AI o o o o o 1943 1950 1956 1952--69 1950s o o 1965 1966--73 o o o o o 1969--79 1980-1986-1987-1995-- McCulloch & Pitts: Boolean circuit model of brain Turing's "Computing Machinery and Intelligence" Dartmouth meeting: "Artificial Intelligence" adopted Look, Ma, no hands! Early AI programs, including Samuel's checkers program, Newell & Simon's Logic Theorist (GPS), Gelernter's Geometry Engine Robinson's complete algorithm for logical reasoning AI discovers computational complexity Neural network research almost disappears Early development of knowledge-based systems AI becomes an industry Neural networks return to popularity AI becomes a science The emergence of intelligent agents University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 18 State-of-the-art AI systems o Deep Blue • Computer chess program defeated world champion Garry Kasparov in 1997 o Automated Theorem Prover EQP • William McCune proved in 1996 a mathematical conjecture (Robbins conjecture) unsolved for decades o During the 1991 Gulf War, US forces deployed DART an AI logistics planning and scheduling program that involved up to 50,000 vehicles, cargo, and people o Google • The search engine employs AI technology such as machine learning, information retrieval, etc. University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 19 State-of-the-art AI systems o DARPA grand challenge 2005-2007 • Stanley (Stanford) autonomous vehicle finished a 132 mile offroad course in less than 7 hours (won the $2,000,000 prize) • Boss (CMU) autonomous vehicle won the 2007 DARPA Urban Challenge in 2007 (60 miles urban area course) o NASA Spirit and Opportunity Mars rovers • 2003-2009 the two rovers operated autonomously on Mars o ROBOCUP • 1993 – present: autonomous soccer robots competition University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 20 Agents Agents and environments o Rationality o PEAS (Performance measure, Environments, Actuators, Sensors) o Environment types o Agent types o University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 21 Agents o An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators o Human agent • Sensors: eyes, ears, and other organs • Actuators: legs, hands and other body parts o Robotic agent • Sensors: cameras and infrared range finders • Actuators: various motors University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 22 Agents and environments o The agent function maps from percept histories to actions [f: P* A] o The agent program runs on the physical architecture to produce f (ie, implements f) o Agent = architecture + program University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 23 Vacuum cleaner world o o Percepts: location and dirt (e.g., [A, dirty]) Actions: Left, Right, Suck, No-Op University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 24 Vacuum cleaner world Percept sequence Action [A, Clean] Right [A, Dirty] Suck [B, Clean] Left [A, Clean], [A, Clean] Right [A, Clean], [A, Dirty] Suck [A, Clean, [A, Clean], [A, Dirty] Suck … … Partial tabulation of the agent function f University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 25 Rational agents o An agent should strive to "do the right thing", based on what it can perceive and the actions it can perform. • The right action is the one that will cause the agent to be most successful according to some Performance Measure: ie, an objective criterion for success of an agent's behavior o Example of performance measures: • performance measure of a vacuum-cleaner agent could be: amount of dirt cleaned up, amount of time taken, amount of electricity consumed, amount of noise generated etc. University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 26 Rational (intelligent) agents o Rational Agent • For each possible percept sequence, a rational agent should select an action that is expected to maximize its performance measure, given the evidence provided by the percept sequence and whatever built-in knowledge the agent has University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 27 Rational (intelligent) agents o Ability to interact with the real world • to perceive, understand, and act • e.g., speech recognition and understanding and synthesis, image understanding, ability to take actions which have an effect o Knowledge Representation, Reasoning and Planning • modeling the external world, given input • solving new problems, planning and making decisions • ability to deal with unexpected problems, uncertainties o Learning and Adaptation • we are continuously learning and adapting • our internal models are always being “updated” e.g. a baby learning to categorize and recognize animals University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 28 PEAS: Performance, Environment, Actuators, Sensors o To design a rational agent we must specify the task environment o Example: designing an automated taxi • Performance measure? Safe, fast, legal, comfortable trip, maximize profit • Environment? Roads, other traffic, pedestrians, customers, weather • Actuators? Steering, accelerator, brake, signal, horn, navigation display • Sensors? Cameras, sonar, speedometer, GPS, odometer, engine sensors University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 29 Environment types o Fully observable vs. partially observable • Agent’s sensors give access to the complete state of the environment at each point in time Convenient, because the agent need not maintain any internal state to keep track of the world e.g., chess player is fully observable, taxi driver is partially observable o Deterministic vs. stochastic • If the next state of the environment is completely determined by the current state e.g., taxi driver is stochastic (cannot predict traffic, a tire may blow out), vacuum cleaner and chess player are deterministic University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 30 Environment types o Episodic vs. sequential • In an episodic task environment, the agent’s experience is divided into atomic episodes. The next episode does not depend on the actions taken in previous episodes. In sequential environments, the current decision may affect all future decisions. e.g., part-picking robot on the assembly line is episodic, chess player and taxi driver are sequential o Static vs. dynamic • If the environment can change while the agent is deliberating then it is called dynamic, otherwise it is static e.g., taxi driver is dynamic (the other cars and taxi are moving while the agent is deliberating about the next move), crossword puzzle is static (the grid does not change) University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 31 Environment types o Discrete vs. continuous • The discrete/continuous distinction can be applied to the state of the environment, to the way time is handled, and to the percepts and actions of the agent e.g., chess player is discrete-state (finite number of distinct states) and it also has discrete percepts and actions; taxi driver is a continuous state, continuous-time problem (speed and location of the taxi and other vehicles have continuous real values) and continuous actions (steering angle, etc.) o Single vs. multi-agent e.g., crossword puzzle is single agent, chess player involves two agents (competitive multi-agent environment), taxi driver is also multi-agent (cooperative multi-agent environment to avoid collisions) University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 32 Examples Solitaire Backgammon Part-picking robot Taxi Observable? Yes Yes Partly No Deterministic? Yes No No No Episodic? No No Yes No Static? Yes Semi No No Discrete? Yes Yes No No Agents? Single Multi Single Multi The environment type largely determines the agent design The real world is (of course) partially observable, stochastic, sequential, dynamic, continuous and multi-agent University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 33 Agent types o Four basic types in order of increasing generality • Simple reflex agents • Reflex agents with state • Goal-based agents • Utility-based agents o All these can be turned into learning agents University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 34 Agent types o Example: automated taxi agent o Simple reflex • If car-in-front-is-breaking then initiate-breaking o Reflex with state (keeps track of the world) • If car-in-front-is-breaking and on motor-way then initiate-breaking • needs internal state o Goal-based • If car-in-front-is-breaking and needs to get to hospital then go to adjacent lane and plan • search and planning o Utility-based • If car-in-front-is-breaking and on motor-way and needs to get to hospital alive then search of a way to get to the hospital that will make your passengers happy • needs utility function that maps a state to a real function (am I happy?) University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 35 Summary o What is Artificial Intelligence? • Modeling humans thinking, acting, should think, should act o Brief history of AI o Intelligent agents • We want to build agents that act rationally o Real-World Applications of AI • AI is alive and well in various “every day” applications Many products, systems, have AI components o Assigned Reading • Chapters 1 and 2 in the RN textbook University College Cork (Ireland) Department of Civil and Environmental Engineering R. Marinescu 20-October-2009 page 36