Catalogue of Modules, University of Nottingham

G54DIA Designing Intelligent Agents
(Last Updated:03 May 2017)

Year  13/14

Total Credits: 10

Level: Level 4

Target Students:  MSc and Part III UG students in the School of CS and Part II UG students on the BSc and MSci Computer Science with Artificial Intelligence.Also available to Part II UG students in the School of CS subject to Part I performance.Also available to students from other Schools with the agreement of the module convenor.

This module is part of the Artificial Intelligence theme in the School of CS.  Available to JYA/Erasmus students.

Taught Semesters:

Spring Assessed by end of Spring Semester 

Prerequisites: (or equivalent)

G51IAI Introduction to Artificial Intelligence 

Corequisites:  None.

Summary of Content:  You’ll be given a basic introduction to the analysis and design of intelligent agents, software systems which perceive their environment and act in that environment in pursuit of their goals. Spending around two hours each week in lectures and tutorials, you’ll cover topics including task environments, reactive, deliberative and hybrid architectures for individual agents, and architectures and coordination mechanisms for multi-agent systems.

Method and Frequency of Class:

ActivityNumber Of WeeksNumber of sessionsDuration of a session
Lecture 11 weeks2 per week1 hour
Tutorial 11 weeks1 per week1 hour

Activities may take place every teaching week of the Semester or only in specified weeks. It is usually specified above if an activity only takes place in some weeks of a Semester

Method of Assessment: 

Assessment TypeWeightRequirements
Coursework 1 50 5000 word report of agent programming practical 
Coursework 2 50 5000 word final report 

Dr B Logan

Education Aims:  To develop a basic understanding of the problems and techniques of building intelligent agents, to give an appreciation of the trade-offs inherent in the design of agent-based systems, to illustrate these through a project involving the construction of a simple agent-based system to develop new analysis and design skills appropriate to more complex AI problems.

Learning Outcomes:  Knowledge and Understanding Understanding of the problems and techniques in the design of intelligent agents, knowledge of common agent architectures. Intellectual Skills The ability to understand and logically evaluate agents' requirements and specifications, the ability to analyse agent behaviour in a variety of environments. Professional Skills Enhanced AI programming skills. Transferable Skills Enhanced systems analysis and design skills.

Offering School:  Computer Science

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