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Please pick up a copy of the course syllabus from the front desk. http://www.pami.uwaterloo.ca/~khoury/ece457 ECE457 Applied Artificial Intelligence R. Khoury (2007) Page 1 Introduction to AI ECE457 Applied Artificial Intelligence Spring 2007 Lecture #1 Outline What is an AI? Russell & Norvig, chapter 1 Agents Environments Russell & Norvig, chapter 2 ECE457 Applied Artificial Intelligence R. Khoury (2007) Page 3 Artificial Intelligence Artificial intelligence is all around us Computer players in video games Robotics Expert systems Assembly-line robots, auto-pilot, Mars exploration robots, RoboCup, etc. Medical diagnostics, business advice, technical help, etc. Natural language Spam filtering, translation, document summarization, etc. ECE457 Applied Artificial Intelligence R. Khoury (2007) Page 4 What is an AI? Systems that… Humanly Neural Think networks ELIZA Rationally Theorem proving Deep Blue Act Rationality vs. Humans: emotions, instincts, etc. Thinking vs. acting: Turing test vs. Searle’s Chinese room Engineers (and this course) focus mostly on rational systems ECE457 Applied Artificial Intelligence R. Khoury (2007) Page 5 Act Rationally Perceive the environment, and act so as to achieve one’s goal Not necessary to do the best action There’s not always an absolutely best action There’s not always time to find the best action An action that’s good enough can be acceptable Example: Game playing Sample approach: Tree-searching strategies Problem: Choosing what to do given the constraints ECE457 Applied Artificial Intelligence R. Khoury (2007) Page 6 Think Rationally Uses logic to reach a decision or goal via logical inferences Example: Theorem proving Sample approach: First-order logic Problems: Informal knowledge Uncertainty Search space ECE457 Applied Artificial Intelligence R. Khoury (2007) Page 7 Think Rationally 1. 2. 3. X = Y/Z XZ = Y X=Y X+Z=Y+Z X*Y+X*Z X * (Y + Z) a. b. c. d. e. 4. 5. 6. b² = AH * c a² = BH * c a² + b² = BH * c + AH * c a² + b² = c * (AH + BH) a² + b² = c² b/c = AH/b a/c = BH/a AH + BH = c ECE457 Applied Artificial Intelligence R. Khoury (2007) Page 8 Act Humanly “Turing-test” AI Improve human-machine interactions up to human-human level Drawbacks: In some cases, requires dumbing down the AI Lots of man-made devices work well because they don’t imitate nature ECE457 Applied Artificial Intelligence R. Khoury (2007) Page 9 Think Humanly Cognitive science Neural networks Helps in other fields Computer vision Natural language processing ECE457 Applied Artificial Intelligence R. Khoury (2007) Page 10 Rational Agents An agent has A rational agent has an agent program that allows it to do the right action given its precepts ECE457 Applied Artificial Intelligence Sensors Actions Percepts Sensors to perceive its environment Actuators to act upon its environment Environment Actuators Agent Program R. Khoury (2007) Page 11 Properties of the Environment Fully observable vs. partially observable Deterministic vs. stochastic vs. strategic Translation vs. driving vs. chess with timer Discrete vs. continuous Face recognition vs. chess Static vs. dynamic vs. semi-dynamic Sudoku vs. Yahtzee vs. chess Episodic vs. sequential Chess vs. Stratego Chess vs. driving Single agent vs. cooperative vs. competitive Sudoku vs. sport team vs. chess ECE457 Applied Artificial Intelligence R. Khoury (2007) Page 12 Types of Agents Simple reflex agent Model-based agent Considers what will happen given its actions Utility-based agent Keeps track of perception history Goal-based agent Selects action based only on current perception of the environment Adds the ability to choose between conflicting/uncertain goals Learning agent Adds the ability to learn from its experiences ECE457 Applied Artificial Intelligence R. Khoury (2007) Page 13