brain

CSC480 ARTIFICIAL

INTELLIGENCE

psyche

 

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Dr. Susan Imberman Office Hours:      Office Hours:  :      Tuesday 11:00 - 2:00 PM  1N215

 

Professor Imberman's email:   susan dot imberman at csi dot cuny dot edu  (NO SPACES!! The space is there to thwart any Spam crawlers. Replace the word at with @ and dot with . )

 

SYLLABUS

 

LINK to Norvig and Russell’s Textbook page  - Great resource for studying!!

 

 

Date

Topic and Assignments

1/31

What is AI?  The Turing TEST

Read:  Chapter 1 Text

Articles for today

Download and read from the ACM digital library, "Robots After All" by Hans Moravec The ACM digital library is available from the school's library home page.

Rise of the Robots by Hans Moravec

 Notes for today

 

Assignment 1 - The Turing Test

2/3

A History of AI

Creating the Interactive History of AI

   Wiki Topics

Wiki Project Description

Join our History of AI Wiki - Good Until Feb 9

2/5

Class will start at 5:00 PM

2/10

Read Chapter 2 Text

Do Exercises -Chapter 2,  2.3, 2.4,  2.5, 2.9 text due

Intelligent Agents notes

Read Chapter 3 Text

Turing Test Part 1 due:  2/19/2015

Wikis due 2/26/2015

2/12

No class - Holiday!!!!

2/17

Chapter 3 - Uninformed Search

Uninformed Search notes

2/19

Chapter 3 - Uninformed Search

Uninformed Search notes

2/24

Chapter 3 - Uninformed Search, Informed search

Uninformed Search notes

2/26

Chapter 3 -  Informed Search

Wiki's due

3/3

Read Chapter 3 - Informed Search

Cannibals and Missionaries Due 3/17  Problem 3.9 in your text

Lecture Notes

Informed Search continued

Group HW can be done individually or in a group.  No more than 3 people in a group.  If the HW is done in a group then only one HW set is to be handed in for the entire group.  Everyone in the group will receive the same grade.

History of Ai Questions

Chapter 3   3.6 a, d,  3.15, SAMPLE MIDTERM EXAM  - CLICK HERE  Due 3/10

3/5

Class starts at 5PM

Part II Turing test - Take the survey in BB  Due 3/10

3/10

Go over sample Midterm, Look at Turing test results

3/12

Exam 1 Postponed until Tuesday 3/17

3/17

EXAM TODAY!!!!

Sample Midterm ans pt 1

Sample Midterm ans pt 2

3/19

Class starts at 5:10PM

Heuristics

Assignment:  Solving the 16 Puzzle  Due Due 4/16

3/24

Go over Midterm exam

3/26

AI and Games

Minimax HW

3/31/2015

AI and Games

Minimax HW

 

Online Assignment 1

Watch "The Smartest Computer On Earth".

http://www.pbs.org/wgbh/nova/tech/smartest-machine-on-earth.html

 

Answer the "test" questions in the course documents tab in Blackboard.  In order to get credit for this assignment you must answer 15 out of 20 questions correctly.  Multiple attempts will not be allowed.  Hint - The questions are ordered according to the events in the video. 

 

Related youtube videos you need to watch:

https://www.youtube.com/watch?v=P18EdAKuC1U

 

https://www.youtube.com/watch?v=b2M-SeKey4o

 

Online Assigment 2 - Arduino stuff

 

Download and install the Arduino software - Note this software needs to run under an Administrator account.

 

http://arduino.cc/en/main/software

 

Becoming familiar with the Arduino -

Run the blink program:  https://learn.adafruit.com/adafruit-arduino-lesson-1-blink

 

Look at the Arduino documents in BB.  Read the chapter 6 document and do the "wire" experiments.  I will supply the wire.

 

4/2

Read papers on Watson and Deep Blue in assignment section of BB. 

Compare and contrast Watson and Deep Blue.  Use the "How to Evealuate A Paper" questions as your guide.

Due 4/21

How to Evaluate A Paper

  1. What is the thesis behind the work? 
  2. What domain are we talking about?
  3. Representation?
  4. How does it work? Which Search Algorithms are used?
  5. What scale does it work on?
  6. What is the evaluation method?
  7. Was the contest between Deep Blue and Kasparov, and Watson and the two Jeopardy champions "fair"?  Why or Why not?
  8. Anything else of significance.

 

16 Puzzle due 4/16

Online Assignments 1 and 2 due 4/14

 

Extra Credit - Write a program that solves the 8 queens problem using a genetic algorithm.

Enjoy your spring break!!

4/14

Machine Learning Decision Trees

Entropy and Information Gain

Decision Tree Calculations for Play Tennis

Decision Tree Slides from Tom Mitchell

4/16

CLASS CANCELLED

 

4/21

Decision Trees

 

For exam 2 review do problems 1, 4, 5 and 6 on exam2hw

 

DUE 4/28 Extra Credit I -   2 percentage points added to your grade (May substitute for a missing project)  Show the calculations and the resulting decision tree given by the ID3 algorithm when given the following training data.  The target concept is giveloan

 

income

credit card

ownshome

married

giveloan

<30

yes

yes

yes

yes

30-80

yes

no

no

no

>80

yes

no

no

yes

<30

no

no

yes

no

>80

no

no

yes

yes

>80

no

no

yes

yes

30-80

no

yes

yes

yes

30-80

yes

no

no

no

30-80

yes

no

no

no

<30

yes

no

yes

no

30-80

no

yes

yes

yes

 

What rules are defined by the decision tree??

 

DUE 5/19 Extra credit II - (1 percentage point added to grade May substitute for a missing project)) - Do either A,  B OR C.  Do not do all three.  You will receive credit only for one of them.

 

Choice A - C4.5 is a decision tree algorithm that implements the methods we discussed.  Download and run C4.5 on the play tennis data discussed in class and the restaurant data on page 656 in your text.  Print and hand in the results.  C4.5 can be found at:   http://www.rulequest.com/Personal   Note:  C4.5 is a UNIX program and you will need a UNIX account to run the software.  If you are interested in this project see me so I can get you an account if you don't already have one. 

 

Choice B -   The commercial windows version of C4.5, called See5, is available for download at:  http://www.rulequest.com/download.html    It is limited version of the full software.  This means that it will not work with data that has more than 400 records.  Notwithstanding, this is sufficient for the play tennis and the restaurant data.  Download See5 and print the results from those two datasets

 

Choice C – Use Weka’s J4.8 algorithm to do evaluate the two data files. It can be found at:

http://www.cs.waikato.ac.nz/ml/weka/

4/23

CLASS STARTS AT 5:00 PM

Neural Networks

Neural Network slides from Tom Mitchell

Code for perceptron  

Code to run trained perceptron

Excel file to test perceptron

4/28

sigmoid.cpp

bpnet.txt

mainneuralnet.txt

exam2hw

4/30

Robotics

5/3

Go over exam2hw

5/7

Exam II

5/12

Robotics

Finish building your robot

http://learn.parallax.com/node/192

Attach and test the photosensors.  We will use photosensors that have been shielded and wired.

http://learn.parallax.com/node/255

 

Continue with Robot Project

5/14

Robotics

5/21

Last Robotics day.  Robot Project due