Greg GrudicIntroduction to AI1 Introduction to Artificial Intelligence CSCI 3202 Fall 2007 Greg Grudic.

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Presentation transcript:

Greg GrudicIntroduction to AI1 Introduction to Artificial Intelligence CSCI 3202 Fall 2007 Greg Grudic

Introduction to AI2 Admin Stuff 1 Location:TR 12:30-1:45 ECCR 105 Instructor:Greg Grudic Office:ECOT 525 Office Hours:Wednesdays10:00 to 11:00. Thursdays 2:00 to 3:00. And By Appointment. Phone: Course URL: (under construction...)

Greg GrudicIntroduction to AI3 Admin Stuff 2 Course Textbook: There isn’t one, but good reference books are: –The Elements of Statistical Learning, by Hastie, Tibshirani, Friedman –S. Russell and P. Norvig Artificial Intelligence: A Modern Approach Prentice Hall, 2003, Second Edition Grading: –Group Project: 60% –Homework: 30% –Class participation: 10% Course workload outside of class? –About 3-4 hours per week

Greg GrudicIntroduction to AI4 Admin Stuff 3 Homework Assignments –There will be many small ones and one “bigger” one. –Goal: Test knowledge of basic concepts Class Project –Students work in teams of 4 or 5…. Class Participation –There will be many in class quizzes –You are expected to give your “best answer” to the quiz questions –If you give your “best answer” you will be given credit for the quiz. If not, (or you don’t hand it in), you will NOT be given a credit. –Mark calculated: 10% * (number of quiz credits)/(total number of quizzes). –If you can’t make it to a class me.

Admin Stuff 4 Sending Me Start all subject descriptions with: –CSCI 3202: I will post most slides AFTER Class –So take notes during class and ask questions! Greg GrudicIntroduction to AI5

Greg GrudicIntroduction to AI6 Goal of the Course A fundamental understanding of the basic concepts behind Artificial Intelligence –What does it mean for a machine to exhibit AI? A practical understanding of how to apply AI to real world problems PLEASE ASK QUESTIONS!!!

Greg GrudicIntroduction to AI7 What is an AI System? World Agent Sensing Computation Action

Components of an AI System World –This is where the AI agent lives Agent –Sensing: Takes information from the world –Computation: Makes computations based on what it has sensed (perhaps using a time history of senor readings) –Action: Acts in the world to change the state of the agent within it (towards some purpose). Greg GrudicIntroduction to AI8

What are some common uses (successes) of AI Systems? Web search: google, ask, yahoo…. Loan Applications Marketing Economic Analysis –Stocks to buy…. –Products to produce… –Prices to charge…. –Federal economic policies… Computer Games Criminology Greg GrudicIntroduction to AI9

Greg GrudicIntroduction to AI10 AI System World Agent Sensing Computation Action physical world robotics Internet Computer program game data received from the world Plan actions based on sensor observations and the results of previous actions “Move” the agent to some new state in the worlds

Some AI Systems that are Better Than Humans (1) Checkers –Chinook was the first computer program to win a checkers world championship (using heuristics) –Checkers is now solved ving_checkers.html There is a proof that nothing can now beat this program (no more heuristics) Greg GrudicIntroduction to AI11

Some AI Systems that are Better Than Humans (2) Chess –DEEP BLUE was the first computer program to beat the world chess champion (using powerful computers and a bunch of very good heuristics) –Not yet solved… Greg GrudicIntroduction to AI12

Some AI Systems that are Better Than Humans (3) Backgammon –TD gammon was the first program to beat the worlds best players (Gerald Tesauro) Greg GrudicIntroduction to AI13

Some AI Systems that are Better Than Humans (4) Robotics for manufacturing in structured factories –Many products (cars, computers, etc..) are made using robots Greg GrudicIntroduction to AI14

Some Failures of AI The game GO –Simple rules but very large search space… Expert systems (in general) –These attempted to encode an experts knowledge into an autonomous reasoning systems Robotics in unstructured environments. A robot cannot –Clean my house –Cook when I don’t want to –Wash my clothes –Cut my grass –Fix my car (or take it to be fixed) –i.e. do the things that I don’t feel like doing… Greg GrudicIntroduction to AI15

Greg GrudicIntroduction to AI16 Robotics Robotics is AI in the physical world It is the hardest subfield of AI because robots must sense and act in the physical world The computer revolution has changed the world…. However, the robotics revolution, when it happens, will make the computer revolution pale in comparison

Greg GrudicIntroduction to AI17 A Open Problem in AI/Robotics? “Vision-based autonomous navigation in unstructured outdoor environments” –This is the main research focus of the DARPA LAGR program. Includes 8 teams GaTech, Netscale (NYU), SRI, NIST, API, JPL, UPenn, CU The problem of navigating between 2 GPS waypoints (more than a few hundred metres apart) in unstructured outdoor environments is unsolved!

Greg GrudicIntroduction to AI18 How is it Currently Done? Crusher and, more recently, PerceptTOR

Greg GrudicIntroduction to AI19 What About the DARPA Grand Challenge? Autonomous Navigation in the Desert over a 132 mile course. 5 Teams succeeded! – This was a monumental achievement in autonomous robotics HOWEVER: This was not an unstructured environment! –GPS waypoints were carefully chosen, sometimes less than a meter apart.

Greg GrudicIntroduction to AI20 Environments that DARPA Grand Challenge winners would find challenging:

6/11/2015University of Colorado, ML Based Robotics 21 Our Main Platform (LAGR) WAAS GPS mounted on a collapsible mount E-Stop IR Rangefinder Bumper with dual switches Differential drive Dual stereo cameras

6/11/2015University of Colorado, ML Based Robotics 22 Our LAGR Robot

Next Class 5 minute quiz at the start of class –Hint: think about what differentiates the successes and failures of AI. –Remember – quizzes only counts towards class participation! Robot demo outside Introduce the group project Questions? Greg GrudicIntroduction to AI23