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Artificial Intelligence

Jacky Baltes <jacky.baltes@gmail.com>

Important Updates

  1. Page opened Friday, 11th December 2019

Content

This course covers a variety of topics in artificial intelligence. The course includes complexity analysis, weak search methods, heuristics, A* search, and game playing search. The course investigates several application domains for AI such as

  1. Puzzles and problem solving
  2. Complete information adversarial games
  3. Natural language processing and translation

There is a large practical component to the course. You will implement various artificial intelligence algorithms using python and its associated libraries.

Download and install the Anaconda python distribution from Continuum. Please make sure that you use the 3.5 version of python, not the 2.7 version.

Assessment

Your grade in the course depends on the result of the following assessments:

  1. Midterm Exam: 40%
  2. Final Exam: 60%

Lecture Slides

The following lecture slides are available.

  1. Jacky Baltes Introduction
  2. Introduction to Artificial Intelligence
  3. Introduction to Python Programming
  4. Search
  5. Adversarial Game Search

Assignments

Sample Code

The following are links to some sample code provided for the course.

The sample programs can be found in the  Google course repository, Python programming exercises, and Google Colaboratory Artificial Intelligence.

Code is also available on my github repository Artificial Intelligence

  1. Simple Python Code
  2. Wolf, Sheep, and Cabbage Problem - Depth First Search
  3. Iterative Deepening DFS
  4. Simple robot navigation using A* search

Other Information