TDDA14 AI Programming 2007

Study Guide@lith

Valid for year : 2007

TDDA14	AI Programming, 7,5 ECTS credits. /AI-programmering/ For: C CS D IT
	Prel. scheduled hours: 78 Rec. self-study hours: 122
	Area of Education: Technology Subject area: Computer Science/Computer Engineering
	Advancement level (G1, G2, A): A
	Aim: The aim of the course is to give an introduction to agent-oriented AI programming through the use of robotic soccer (RoboCup). The course introduces fundamental problems and techniques related to the construction of agent-oriented AI-systems. The students should also gain practical experience in solving the problems and implementing and integrating these techniques. The course has three phases. The aim of the first phase is to make the students proficient with RoboCup and the RoboSoc framework which is used to implement the agents. More specific the goals of the first phase are that the students should: be able to describe and explain how multiagent simulations work using RoboCup as the example, be able to use existing frameworks to implement simulated agents, and be able to design and implement a multiagent system consisting of a RoboCup team. The aim of the second phase is to give an overview of problems and solutions in the area of multiagent systema and then focus on a specific problem or technique in order to make an in depth study of it. More specific the goals of the second phase are that the students should: be able 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 critizing existing work in order to make a judgement on the applicability or suitability of the chosen technique or problem, be able to design, implement, and test a multiagent technique in a simulated agent environment as part of a group, and be able to make written and oral presentations of their work. The aim of the third phase is to integrate the work done in the previous phases and create a complete multiagent system. More specific the goals of the third phase are that the students should: be able to integrate existing and new techniques into a single multiagent system, be able to design and implement the control of such a system as part of a group, and be able to make written and oral presentations of their work.
	Prerequisites: (valid for students admitted to programmes within which the course is offered) Introductory course in artificial intelligence. Object-oriented programming, preferably in C++. Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshhold requirements for progression within the programme, or corresponding.
	Supplementary courses: TDDA16 Representation of Knowledge in AI
	Organisation: The course is organised as a number of lectures and seminars combined with practical work. The lectures discuss the practical and theoretical aspects of agent-based AI-systems. The seminars discuss specific solutions to the problems arising during laboratory assignments and are held in cooperation with the students, who will present their problems and solutions. In the laboratory work the students will implement and evaluate AI techniques and also develop their own soccer team.
	Course contents: Implementation and use of multi-agent systems, agent architectures, machine learning, communication, teamwork and coordination among agents.
	Course literature: Wooldridge, Michael (2002) An Introduction to Multiagent Systems. John Wiley & Sons. ISBN 047149691X.
	Examination:
	Laboratory work	5 p	/	7,5 ECTS


Course language is English. Department offering the course: IDA. Director of Studies: Peter Dalenius Examiner: Fredrik Heintz Link to the course homepage at the department Course Syllabus in Swedish

Linköping Institute of Technology
Contact: TFK , val@tfk.liu.se Last updated: 09/15/2007