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.
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.
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.
By the end of the module, students should be able to:
Please see Talis Aspire link for most up to date list.
View reading list on Talis Aspire
|Lectures||30 sessions of 1 hour (20%)|
|Seminars||9 sessions of 1 hour (6%)|
|Private study||111 hours (74%)|
Inclusive of private study, coursework, background reading and revision.
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.
|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.
|On-campus Examination - Resit||100%|
CS404 resit paper
~Platforms - AEP
Written feedback with mark breakdown for programming assignment and report.
Knowledge of Python programming.
This module is Optional for:
This module is Option list A for:
This module is Option list B for: