CS404 Agent Based Systems
CS404-15 Agent Based Systems
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 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 D2
| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
| Programming and report | 25% | No | |
|
Programming and report. Approximately 30 pages. |
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| In-person Examination | 75% | No | |
|
CS404 examination
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Assessment group R3
| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
| On-campus Examination - Resit | 100% | No | |
|
CS404 resit paper
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Feedback on assessment
Written feedback with mark breakdown for programming assignment and report.
Pre-requisites
Knowledge of Python programming.
Courses
This module is Optional for:
- Year 5 of UCSA-G504 MEng Computer Science (with intercalated year)
- Year 1 of TCSA-G5PB Postgraduate Taught Data Analytics (CUSP)
- Year 4 of UCSA-G503 Undergraduate Computer Science MEng
- Year 4 of USTA-G1G3 Undergraduate Mathematics and Statistics (BSc MMathStat)
- Year 5 of USTA-G1G4 Undergraduate Mathematics and Statistics (BSc MMathStat) (with Intercalated Year)
This module is Option list A for:
- Year 5 of UCSA-G504 MEng Computer Science (with intercalated year)
- Year 4 of UCSA-G503 Undergraduate Computer Science MEng
- Year 4 of USTA-G304 Undergraduate Data Science (MSci)
- Year 4 of UCSA-G4G3 Undergraduate Discrete Mathematics
- Year 5 of UCSA-G4G4 Undergraduate Discrete Mathematics (with Intercalated Year)
This module is Option list B for:
- Year 4 of UCSA-G408 Undergraduate Computer Systems Engineering
- Year 5 of UCSA-G409 Undergraduate Computer Systems Engineering (with Intercalated Year)
Further Information
Term 2
15 CATS (7.5 ECTS)
Module Organisers:
Debmalya Mandal
Paolo Turrini