Course syllabus
Spring 2024
Course syllabus, Spring 2024
KursInfo revision no. 3
Title
Distributed Intelligent Systems
Swedish title
Distribuerade intelligenta system
Course code
DA382A
Credits
7.5 credits
Grading scale
UA Excellent (A), Very Good (B), Good (C), Satisfactory (D), Pass (E) or Fail (U)
Language of instruction
Swedish, elements of English can occur.
Decision-making body
Faculty of Technology and Society
Syllabus approval date
2020-01-20
Syllabus valid from
2022-01-17
Level
Basic level
Entry requirements
- 9 credits from DA339A
Main field
Computer Science
Progression level
G1F First cycle, has less than 60 credits in first-cycle course/s as entry requirementsCourse contents
The course contains the following topics:
- Different concepts of intelligent systems
- Overview over agent-based paradigms
- Multi agent-based systems and development platforms
- Reasoning and decision making
- Communication and co-ordination between agents
- Examples of applications
Learning outcomes
Knowledge and understanding
On completion of the course the student shall:
- be able to demonstrate an understanding for the concept of multi-agent systems
Skills and abilities
On completion of the course the student shall:
- be able to contribute to the implementation of a distributed intelligent system
- be able to manage and apply development methodologies for multi-agent systems that communicate and collaborate with one another.
Judgement and approach
On completion of the course the student shall:
- be able to analyze and discuss technical solutions and limitations in the subject described in current research.
Learning activities
Students put the theoretical concepts studied continuously into practice. They are expected to actively participate in small teams that design, implement, and validate the theory in a large complex distributed software project.
Assessment
Students’ fulfillment of learning objectives are examined based on the software produced and on an individual documentation and oral presentation of how their practical work refers to the theoretical concepts taught in the course.
Requirements for pass (scale A-E):
Mandatory active participation in at least 80% of all exercise classes as well as passed software (3 hp).
Passed individual documentation and presentation (4,5 hp).
The final grade for the course is the same as the grade for the individual documentation and presentation.
Course literature and other study materials
Recommended literature:
- Wooldridge, Michael J. (2009).An introduction to multiagent systems. 2nd ed. Chichester, U.K.: John Wiley & Sons
Supplementary literature in the form of relevant scientific articles are provided during the course.
KursInfo revision no. 3