Introductory description

Agent-based systems offer a new paradigm for computer science, based around a strong theoretical foundation and with a large number of practical deployed applications.

Module web page

Module aims

This module will provide a context for agent-based systems in terms of the recent and developing computing landscape of distributed information and processing resources, and will describe fundamental techniques and systems, illustrating them with real-world applications.

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Overview: definitions of agents, distributed AI and agents, intelligent agents, multi-agent systems, cooperation, agent application areas.

Logic-based agents: actions, goals and strategies.

Decision-making agents: expected utility and decisions.

Game-theoretic agents: equilibria and rationality.

Learning-agents: Markov Decision Processes, policy approximation and opponent modelling.

Social-agents: Cooperative decision-making, matching and networks.

Learning outcomes

By the end of the module, students should be able to:

Students will learn the basic methodologies for the design and the analysis of multi-agent systems, in competitive and cooperative interaction, both from the theoretical and the practical point of view.

Indicative reading list

Please see Talis Aspire link for most up to date list.

View reading list on Talis Aspire

Subject specific skills

Logical reasoning;
Problem Solving;

Transferable skills

Problem Solving;
Logical reasoning;
Self-directed learning.

Study time

Type	Required
Lectures	30 sessions of 1 hour (20%)
Seminars	10 sessions of 1 hour (7%)
Private study	110 hours (73%)
Total	150 hours

Private study description

Inclusive of private study, coursework, background reading and revision.

Costs

No further costs have been identified for this module.

You do not need to pass all assessment components to pass the module.

Students can register for this module without taking any assessment.

Assessment group D1

	Weighting	Study time
Programming and report	25%
Programming and report. Approximately 30 pages. This assignment is worth more than 3 CATS and is not, therefore, eligible for self-certification.
In-person Examination	75%
CS924 examination Answerbook Pink (12 page) Students may use a calculator

Assessment group R3

	Weighting	Study time
On-campus Examination - Resit	100%
CS924 resit paper Answerbook Pink (12 page) Students may use a calculator

Feedback on assessment

Written feedback with mark breakdown for programming assignment and report.

Past exam papers for CS924

Pre-requisites

Knowledge of Python programming.

Courses

This module is Optional for:

Year 1 of TCSA-G5PD Postgraduate Taught Computer Science
Year 1 of TCSA-G5PA Postgraduate Taught Data Analytics
Year 1 of TMAA-G1PF Postgraduate Taught Mathematics of Systems

CS924-15 Agent Based Systems