TDDD10 AI Programming

Course information

Course Goals

The AI Programmering course covers fundamental problems and techniques for constructing agent-oriented AI-systems in particular multiagent systems. The main example and application domain is simulated robotic soccer in the RoboCup domain.

The goals of the course are that each student should

• be able to list and explain important problems and techniques in the area of multiagent systems,
• be able to evaluate a technique or solutions to a problem in the area of multiagent systems, including summarizing and criticizing existing work in order to make a judgment on the applicability or suitability of the chosen technique or solution,
• be able to design, implement, and test a multiagent technique in a simulated agent environment as part of a group,
• be able to make written and oral presentations of their work, and
• be able to design and implement a multiagent system in the form of a RoboCup team.

Examination

The examination consists of three related assignments:

1. The Skill Assignment
2. The Team Assignment
3. The Individual Assignment

The first two assignments are done in groups of 2-3 students while the last assignment is done individually. Each group should be registered in WebReg.

An overview of the course and the three assignments.

The division of time looks like this:

Skill Assignment:	8h Le	2h Se	28h La	12h homework
Team Assignment:	6h Le	4h Se	20h La	20h homework
Individual Assignment:	6h Le	4h Se	12h La	38h homework
Total:	20h Le	10h Se	60h La	70h homework
Sum:	160h = 6 credits

Page responsible: Fredrik Heintz
Last updated: 2012-08-22