Module Details

The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title Multi-Agent Systems
Code CSCK504
Coordinator Dr F Grasso
Computer Science
Year CATS Level Semester CATS Value
Session 2022-23 Level 7 FHEQ Whole Session 15


1. To provide students with a thorough and comprehensive understanding of the computer science domain of multi-agent systems.

2. To enable students to critically evaluate current theories and methods in multi-agent system design and their application to a wide variety of contexts.

3. To equip students with technical knowledge and skills to develop and deploy multi-agent system solutions to solve real world problems.

Learning Outcomes

(M1) An in depth understanding of the area of multi-agent systems, their theoretical underpinning and practical applications.

(M2) A comprehensive understanding of the difference between the multi-agent paradigm and the more conventional approaches to complex systems design.

(M3) An ability to analyse real world problems for which a multi-agent system approach is appropriate, and formulate a solution.

(M4) An ability to critically evaluate and deploy software tools and skills for the implementation of multi-agent systems.

(S1) Communication skills in electronic as well as written form.

(S2) Self direction and originality in tackling and solving problems within the domain of Computer Science, and an ability to act autonomously in planning and implementing solutions in a professional manner.

(S3) Experience of working in development teams and the leadership of such teams.

(S4) Group working, respecting others, co-operating, negotiating, awareness of interdependence with others.



Week 1. What is an agent. Agents vs objects. Agents vs expert systems. The notion of autonomy. Intelligent agents.

Week 2. Reasoning with agents. Reactive and Hybrid agents. Layered agents. Rational agents: Belief/Desire/Intention

Week 3. Multi-agent systems. Agent-oriented analysis and design. Methodologies for designing and creating multi-agent systems.

Week 4. Agent Communication. Speech acts. Agent communication languages. KQML, FIPA.

Week 5. Understanding each other. Ontologies and ontology languages. XML. Description Logics.

Week 6. Multiagent decision making: coalitions, cooperative and adversarial interaction. Prisoner's dilemma. Nash equilibria.

Week 7. Negotiating and bargaining. Voting and auctions. Argumentation. Abstract argument systems.

Week 8. Applications. Exemplar applications of multi-agent system technology. Criteria for determining when a multi-agent solution is appropriate.

Teaching and Learning Strategies

The mode of delivery is by online learning, facilitated by a Virtual Learning Environment (VLE). This mode of study enables students to pursue modules via home study while continuing in employment. Module delivery involves the establishment of a virtual classroom in which a relatively small group of students (usually 10-25) work under the direction of a faculty member. Module delivery proceeds via a series of eight one-week online sessions, each of which comprises an online lecture, supported by other eLearning activities, posted electronically to a public folder in the virtual classroom. The mode of learning includes a range of required and optional eLearning activities, including but not limited to: lecture casts, live seminars, self-assessment opportunities, and required and suggested further reading and try-for-yourself activities. Communication within the virtual classroom is asynchronous, preserving the requirement that students are able to pursue the module in their own time, within the weekly time-frame of each online session. An important element of the module provision is active learning through collaborative, cohort-based, learning using discussion fora where the students engage in assessed discussions facilitated by the faculty member responsible for the module. This in turn encourages both confidence and global citizenship (given the international nature of the online student body).

Teaching Schedule

  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 24


Timetable (if known)              
Private Study 86


EXAM Duration Timing
% of
Penalty for late
CONTINUOUS Duration Timing
% of
Penalty for late
Report: Multi-agent systems group project resulting in a demonstrable system and a group report describing and analysing the system.    30       
Programming: Individual software solution to a multi-agent systems’ problem resulting in a demonstrable system and supporting demonstration, analysis and explanation in the form of a short video (Expe  12    30       
Discussion question 2: Participate actively in an online discussion on a specific topic related to multi-agent systems, demonstrating an understanding of the key issues and showing original thought.    20       
Discussion Question 1: Participate actively in an online discussion to critically discuss experiences and opinions within the cohort relating to multi-agent systems.    20       

Recommended Texts

Reading lists are managed at Click here to access the reading lists for this module.