DSP722 Multiagent Systems

Code DSP722
Name Multiagent Systems
Status Compulsory/Courses of Limited Choice
Level and type Post-graduate Studies, Academic
Field of study Computer Science
Faculty
Academic staff Egons Lavendelis
Credit points 4.0 (6.0 ECTS)
Parts 1
Annotation One of developing directions of artificial intelligence is based on the intelligent agent paradigm. Its goal is to create systems that act rationally. Communities of agents form multiagent systems that form the basics of distributed intelligent computing. Autonomous robot systems are important application of such systems. The course considers the main topics of multiagent systems and methodologies of their development. Main emphasis is on social capabilities of agents, like multiagent interaction, communication and cooperation. The course gives an overview of applications of multiagent systems and an insight in implementation of robotics as multiagent systems..
Contents
Content Full- and part-time intramural studies Part time extramural studies
Contact hours Independent work Contact hours Independent work
Multiagent systems and the concept of agent in the context of multiagent systems 4 0 0 0
Multiagent interactions 6 2 0 0
Reaching agreements in multiagent systems 10 5 0 0
Communication in multiagent systems 6 3 0 0
Co-operation in multiagent systems 8 4 0 0
Multiagent architectures 4 2 0 0
Agent oriented software engineering methodologies 12 2 0 0
Applications of multiagent systems 8 4 0 0
Robotic multiagent systems 6 4 0 0
Design and implementation of a multi-agent system 2 48 0 0
Examination and consultation before (summary of the course) 6 14 0 0
Total: 72 88 0 0
Goals and objectives
of the course in terms
of competences and skills 		The goal of the course is to give basic knowledge and to acquire skills how to evaluate and choose appropriate methodology and methods for the design and development of robotic multiagent system.
Learning outcomes
and assessment 		Students are able to determine utilities, preferences and dominant strategies - Questions of the theoretical part of examination
Students are able to use interaction and negotiation protocols in multiagent systems and to choose appropriate protocols, including the most appropriate auctions - Practical work, defence of course work, questions of the theoretical part of examination
Students have a good knowledge of agent communication languages - Practical work, defence of course work
Students are able to create a multiagent system for cooperative work - Practical work, defence of course work, questions of the theoretical part of examination
Students have knowledge about agent oriented software engineering and concepts used in it - Practical work, defence of course work, questions of the theoretical part of examination
Students are able to evaluate and to choose suitable methodology for the development of multiagent system - Practical work, defence of course work, questions of the theoretical part of examination
Students are able to design multliagent systems, including robotic multiagent systems - Practical work, defence of course work, questions of the theoretical part of examination
Students have good knowledge about possible applications of multiagent systems. They will be capable to evaluate appropriateness of multiagent systems in various application domains - Practical work, defence of course work, questions of the theoretical part of examination
Evaluation criteria of study results
Examination - 50%
Course work - 30%
Practical works - 20%
 
Course prerequisites Students must know algorithms used in artificial intelligence, like uninformed and informed search. They should be familiar with knowledge representation schemas such as first order logic, production rules, semantic networks, conceptual graphs and frames. Basic notions of intelligent agents, agent characteristics and environments, should be known as well.
Course planning
Part CP ECTS Hours Tests
Lectures Practical Lab. Test Exam Work
1 4.0 6.0 3.0 1.0 0.0 *
[Extended course information PDF]