TDDD10 AI Programming
The AI Programming course covers fundamental problems and techniques for constructing agent-oriented AI-systems in particular Multi-agent systems. The main example and application domain is simulated urban search and rescue (USAR) 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 Multi-agent systems,
- be able to evaluate a technique or solutions to a problem in the area of Multi-agent 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 Multi-agent 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 Multi-agent system in the form of a RoboCup team.
Please, see LiTH Study Guide.
Division of time
|Initial labs:||28h La||12h ho|
|Team Assignment:||20h La||4h Se||20h ho|
|Individual Assignment:||12h La||8h Se||36h ho|
|Total:||20h Le||12h Se||60h La||68h ho|
|Sum:||160h = 6 credits|
|Legend:||le = lectures se = seminar
ho = homework la = labs
Page responsible: Cyrille Berger
Last updated: 2016-09-22