Computer Science Department

CS4341 ❏ Artificial Intelligence


There are four projects. They will all be described separately in detail on separate web pages. The due dates are given in the Schedule. Brief project descriptions are given below. As is appropriate for a 4000-level class, the projects will probably not be completely described by the handouts. You will probably need more information. Some from the book; some from me in class and office hours. You'll need to invent the rest. Start designing the project immediately you get the project description, otherwise you'll be up all night the day before it's due, and I'll say "I told you so", and you'll say "&*^%$#* &^%$", and we'll both get annoyed.

Project 0 - Setting the Stage
(Takes about 1 week)

Write a program to investigate the performance of some basic searches in a simulated landscape.

Project 1 - A Rule Interpreter & an Intelligent System
(Takes about 2 weeks)

Write a program, a Rule Interpreter (RI), that will take a set of Situation-Action rules and will apply them to a set of facts. This is a simple general-purpose problem-solving system. Then write an intelligent system (IS), using rules and the RI, to do some basic intelligent task in the simulated landscape. Sample tasks might be Design, Diagnosis, or Criticism, for example. The domain is the situation in the landscape (e.g., vehicles and obstacles). So, some domain/task combinations might be landscape Design (e.g., designing and placing obstacles to satisfy some requirements), or landscape Diagnosis (e.g., hypothesizing the existence of a problem in the landscape).

Project 2 - A* & Constraint Satisfaction
(Takes about 1 week)

Write programs to demonstrate the use of A* as well as to use the Min-Conflicts heuristic for a contraint satisfaction problem.

Project 3 - A Genetic Algorithm Learning System
(Takes about 2 weeks)

Write a Genetic Algorithm (GA) learning system that will discover the most effective combination of search vehicles of different types. The search is carried out in the simulated landscape. The search team can be made up of a small number of vehicles selected from different types. The best team finds lost children quickly and with low cost. The GA will evaluate different teams until the most effective team is produced.