Web Page: http://www.seas.upenn.edu/~cis521/ -- but everything is on blackboard

Textbook:

Artificial Intelligence: A Modern Approach

(Third Edition) 2009

Stuart Russell and Peter Norvig

Prentice Hall Series in Artificial Intelligence

Grading:

40% Homeworks

25% Midterm

35% Final

Homework:

Homework will be due at 9:00 a.m. on specified dates

Late homeworks will be penalized unless an extension has been granted in advance :

-- 15% reduction if 0-24 hours (1 day) late

-- 30% reduction if 24-48 hours (2 days) late

-- 45% reduction if 72 (3 days) hours late

-- no credit if mmore than 96 hours (4 days) late

Most homework will be submitted on blackboard; Late hard-copy homeworks can be handed in to Cheryl in 502 Levine.

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Lecture Notes are on blackboard in Micrososft Powerpoint You can view them with either Microsoft PowerPoint or the free Microsoft PowerPoint Viewer.

Module 0: Introduction 
AIMA Textbook: Chapts 1-2

• Introduction
  
• Intelligent Agents
  
• Python Programming

Module 1: Search
AIMA Textbook: Chapts 3-6

• Search
  
• Adversarial Search
  
• CSP
  

Module 2: Knowledge Representation and Logic
AIMA Textbook: Chapts 8-9

• Logical Agents & Propositional Logic
• First Order Logic

Module 3: Machine Learning and Natural Language Processing
AIMA Textbook: Chapts 13-15, 18, 22

• Introduction to Probability
• Bayesian Networks
• Hidden Markov Models
• Perceptrons and Support Vector Machines
• Introduction to Natural Language Processing

Dessert: AI - The Future of AI and Humanity



Final: as scheduled during finals wweek

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HOMEWORK ASSIGNMENTS

Homework will be a mixture of short answer questions longer programming assignments in python. Hard copy is to be handed in in class and executable code submitted through blackboard


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OTHER RESOURCES

Python Resources

• http://www.python.org/
  and especially
  • the Library Reference at http://docs.python.org/tut/tut.html
  • and the tutorial at http://docs.python.org/tut/tut.html
• http://www.rexx.com/~dkuhlman/python_101/python_101.html
• http://www.rexx.com/~dkuhlman/python_201/python_201.html
• http://www.awaretek.com/tutorials.html
• http://openbookproject.net/thinkcs/python/english2e/
• Downloadable versions of the book "Dive into Python"
• You can access O'Reily's Safari website, which has books such as Learning Python, Programming Python, Python in a Nutshell, and Python Cookbook, from the Penn library e-resources page. (Type "python" in the search box when you finally get to the Safari page.)

Textbook Resources

• Website for: Artificial Intelligence: A Modern Approach
  (http://aima.cs.berkeley.edu/)
   

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For more information, please contact ungar@cis.upenn.edu