Introduction to Artificial Intelligence CS 438 Spring 2008 Today –AIMA, Chapter 1 –Defining AI Next Tuesday –Intelligent Agents –AIMA, Chapter 2 –HW: Problem.

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Presentation transcript:

Introduction to Artificial Intelligence CS 438 Spring 2008 Today –AIMA, Chapter 1 –Defining AI Next Tuesday –Intelligent Agents –AIMA, Chapter 2 –HW: Problem 2.5 ADD: “A vacuum cleaning robot”

Goals of Artificial Intelligence Human Performance Ideal Performance ThinkingSystems that think like human Cognitive Science Systems that think rationally Formal Logic BehaviorSystems that act like humans Turing Test Systems that act rationally Heuristic Reasoning

Thinking Humanly Cognitive Science –Construct theories of how the human mind works

Thinking Humanly The Game of 15 1.Two players alternate in picking numbers from 1 to 9 2.Each number may only be used once 3.The player who picks 3 numbers that add up to exactly 15 wins

Thinking Humanly Nine-cell magic square is equivalent to Tic-Tac-Toe Same game, but magic square representation is easier for a computer to reason with, Tic-Tac-Toe Board is easier for a human to reason with

Thinking Rationally Rationality –Thinking “right” or “correctly” Thinking Rationally –Logic: formal laws of thought Patterns of representing knowledge that guarantee every inference is correct

Thinking Rationally Deduction –Aristotle is a man –All men are mortal –Therefore: Aristotle is mortal Induction –Aristotle is a man –Aristotle is mortal –Therefore: All men are mortal Abduction –All men are mortal –Aristotle is mortal –Therefore: Aristotle is a man

Thinking Rationally Problems as a KR –Informal knowledge is difficult to state in formal terms –Small problems can quickly exhaust computational resources –Not always a provably correct thing to do

Acting Humanly Turing Test –An operational definition of intelligence –Can a computer carry on a conversation well enough to convince you that you are talking to another human –Loebner Prize –What is needed to pass the TT NLP (Natural Language Processing) KR Automated Reasoning Machine Learning

Total Turing Test Computer Vision (or other senses) Computer manipulation Robot –A machine able to extract information from its environment and use knowledge about its world to move safely in a meaningful manner –Physically embodied Intelligent Agent As opposed to a “brain-in-a-box”

What does it take to get an intelligent robot to do a simple task? Robot Parts: Two Arms, Vision, and Brain The Brain can communicate with all parts Arms can take commands as left, right, up, down, forward, and backward Arms can answer yes/no about whether they are touching something but cannot distinguish what they are touching The vision system can answer any question the brain asks, but cannot volunteer information. The vision system can move around to get a better view.

Why is this simple task so difficult? Coordination is difficult Indirect feedback Updating knowledge about the environment Unexpected events –Need to re-plan Different coordinate systems need to be resolved –Box-centered and arm-centered

Acting Rationally Acting to achieve one’s goals given one’s beliefs –Given the information it knows at the time and its knowledge base it performs THE BEST action to achieve its goals –Uncertainty Making the action with the best expected outcome –Bounded rationality Determining the best action with limitations of resources of time and/or memory AI: The construction of rational agents

Physical Symbol System hypothesis "A physical symbol system has the necessary and sufficient means of general intelligent action.“ A. Newell & H. Simon

Intelligent Agents (IA’s) are Physical Symbol Systems –Symbols and symbols structures that can be manipulated syntactically by a set of processes –The symbol structure can be interpreted semantically