SLIDE 1CS 362 Artificial Intelligence Hassan Najadat Jordan University of Science & Technology

SLIDE 2CS 362 Outline Course Overview What is AI ? A brief history The state of the art

SLIDE 3CS 362 Course Overview Intelligent agent Problem Solving –Solving problems by searching –Informed Search and Exploration –Constraint Satisfaction Problems –Adversarial Search Logical system –Logical Agent –First Order Logic –Inference in First-Order Logic –Knowledge Representation Learning from Observations

SLIDE 4CS 362 “Like People”“Rationally” Think Cognitive Science Laws of Thought ActTuring TestRational Agents What is AI ?

SLIDE 5CS 362 What is AI ? Systems that think like humansSystems that think rationality ``The exciting new effort to make computers think... machines with minds, in the full and literal sense'' (Haugeland, 1985) ``The automation of activities that we associate with human thinking, activities such as decision-making, problem solving, learning...'' (Bellman, 1978) ``The study of mental faculties through the use of computational models'' (Charniak and McDermott, 1985) ``The study of the computations that make it possible to perceive, reason, and act'' (Winston, 1992) Systems that act like humansSystems that act like rationality ``The art of creating machines that perform functions that require intelligence when performed by people'' (Kurzweil, 1990) ``The study of how to make computers do things at which, at the moment, people are better'' (Rich and Knight, 1991) ``A field of study that seeks to explain and emulate intelligent behavior in terms of computational processes'' (Schalkoff, 1990) ``The branch of computer science that is concerned with the automation of intelligent behavior'' (Luger and Stubblefield, 1993)

SLIDE 6CS 362 Acting humanly: The Turing Test approach The Turing Test, proposed by Alan Turing (Turing, 1950), was designed to provide a satisfactory operational definition of intelligence. The computer would need to possess the following capabilities: 1.Natural language processing to enable it to communicate successfully in English (or some other human language); 2.Knowledge representation to store information provided before or during the interrogation; 3.Automated reasoning to use the stored information to answer questions and to draw new conclusions; 4.Machine learning to adapt to new circumstances and to detect and extrapolate patterns. To pass the total Turing Test, the computer will need Computer Vision Robotics

SLIDE 7CS 362 Example Natural Language (NL) Processing 1.noun 2.verb 3.determiner 4.adjective 5.adverb 6.pronoun s --> det, noun, verb, det, noun. a better version –s --> np, verb. s --> np, verb, np. np --> det, adj*, noun. np --> proper-name. np --> pronoun.

SLIDE 8CS 362 Thinking humanly: The cognitive modeling approach - Program thinks like a human..! We need to get inside the actual workings of human minds. There are two ways: –through introspection--trying to catch our own thoughts as they go by— –or through psychological experiments. GPS -``General Problem Solver'' –(GPS) A procedure and program developed by Allen Newell, J. C. Shaw, and Herbert Simon. –GPS attains an objective by using recursive search and by applying rules to generate the alternatives at each branch in the recursive expansion of possible sequences. – GPS uses a procedure to measure the "distance" from the goal.

SLIDE 9CS 362 Thinking rationality: The Logical approach Ensure that all actions performed by computer are justifiable (“rational”) Rational = Conclusions are provable from inputs and prior knowledge Problems: –Representation of informal knowledge is difficulty –Hard to define “provable” plausible reasoning –Combinatorial explosion: Not enough time or space to prove desired conclusions. Facts and Rules in Formal Logic Theorem Prover

SLIDE 10CS 362 Acting rationally: The rational agent approach Rational behavior : doing the right thing ( that which is expected to maximize goal achievement, given the available information). Agent Program Agent and Program Rational Agent is one that acts to achieve the best outcomes or, when there is uncertainty, the best expected outcome. Rational agents do the best they can given their resources

SLIDE 11CS 362 Rational Agents Adjust amount of reasoning according to available resources and importance of the result This is one thing that makes AI hard very few resourceslots of resources no thought “reflexes” Careful, deliberate reasoning limited, approximate reasoning

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SLIDE 14CS 362 Areas of Study in AI Reasoning, optimization, resource allocation –planning, scheduling, real-time problem solving, intelligent assistants, internet agents Natural Language Processing –information retrieval, summarization, understanding, generation, translation Vision –image analysis, recognition, scene understanding Robotics –grasping/manipulation, locomotion, motion planning, mapping

SLIDE 15CS 362 Where are we now? SKICAT: a system for automatically classifying the terabytes of data from space telescopes and identifying interesting objects in the sky. 94% classification accuracy, exceeds human abilities. Deep Blue: the first computer program to defeat champion Garry Kasparov. Pegasus: a speech understanding program that is a travel agent (1-877-LCS-TALK). Jupiter: a weather information system ( TALK) HipNav: a robot hip-replacement surgeon.

SLIDE 16CS 362 Where are we now? Navlab: a Ford escort that steered itself from Washington DC to San Diego 98% of the way on its own! google news: autonomous AI system that assembles “live” newspaper DS1: a NASA spacecraft that did an autonomous flyby an asteroid. Credit card fraud detection and loan approval Search engines: automatic classification and indexing of research papers. Proverb: solves NYT puzzles as well as the best humans.

SLIDE 17CS 362 Surprises in AI research Tasks difficult for humans have turned out to be “easy” –Chess –Checkers, Othello, Backgammon –Logistics planning –Airline scheduling –Fraud detection –Sorting mail –Proving theorems –Crossword puzzles

SLIDE 18CS 362 Surprises in AI research Tasks easy for humans have turned out to be hard. –Speech recognition –Face recognition –Composing music/art –Autonomous navigation –Motor activities (walking) –Language understanding –Common sense reasoning (example: how many legs does a fish have?)