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TDDD10 AI Programming

Course information

Course Goals

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.

Syllabus

Please, see LiTH Study Guide.

Division of time

Lectures: 20h Le
Initial labs: 28h La12h ho
Team Assignment: 20h La4h Se20h ho
Individual Assignment: 12h La8h Se36h ho
Total: 20h Le12h Se 60h La68h ho
Sum: 160h = 6 credits
Legend: le = lectures se = seminar
ho = homework la = labs

Page responsible: Cyrille Berger
Last updated: 2014-08-27