Please pick up a copy of the course syllabus from the front desk.

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 • Computer players in video games • Robotics • Assembly-line robots, auto-pilot, Mars exploration robots, RoboCup, etc. • Expert systems • Medical diagnostics, business advice, technical help, etc. • Natural language • Spam filtering, translation, document summarization, etc. • Artificial intelligence is all around us ECE457 Applied Artificial Intelligence R. Khoury (2007) Page 4

What is an AI? • Systems that… • 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 • X = Y/Z  XZ = Y • X = Y  X + Z = Y + Z • X * Y + X * Z  X * (Y + Z) • b/c = AH/b • a/c = BH/a • AH + BH = c • b² = AH * c • a² = BH * c • a² + b² = BH * c + AH * c • a² + b² = c * (AH + BH) • a² + b² = c² 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 • Sensors to perceive its environment • Actuators to act upon its environment • A rational agent has an agent program that allows it to do the right action given its precepts Environment Percepts Actions Sensors Actuators Agent Program ECE457 Applied Artificial Intelligence R. Khoury (2007) Page 11

Properties of the Environment • Fully observable vs. partially observable • Chess vs. Stratego • Deterministic vs. stochastic vs. strategic • Sudoku vs. Yahtzee vs. chess • Episodic vs. sequential • Face recognition vs. chess • Static vs. dynamic vs. semi-dynamic • Translation vs. driving vs. chess with timer • Discrete vs. continuous • 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 • Selects action based only on current perception of the environment • Model-based agent • Keeps track of perception history • Goal-based agent • Considers what will happen given its actions • Utility-based agent • 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

Please pick up a copy of the course syllabus from the front desk.