Total Credits: 10
Level: Level 4
Target Students: MSc and Part III undergraduate students in the School of Computer Science and Part II undergraduate students on the BSc and MSci Computer Science with Artificial Intelligence. Also available to Part II undergraduate students in the School of Computer Science subject to Part I performance. Also available to students from other Schools with the agreement of the module convenor. Available to JYA/Erasmus students.
|Spring||Assessed by end of Spring Semester|
Prerequisites: (or equivalent)
|G51IAI||Introduction to Artificial Intelligence|
Summary of Content:
This module is part of the Intelligent Systems theme in the School of Computer Science.
This module gives 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. It synthesises topics from various sub-fields of AI and acts as an introduction to the problems of combining the techniques developed in these areas into a single intelligent agent with broad competence. Topics covered include: task environments, reactive, deliberative and hybrid architectures for agents, and multi-agent systems.
Method and Frequency of Class:
|Activity||Number Of Weeks||Number of sessions||Duration of a session|
|Lecture||11 weeks||2 per week||1 hour|
|Tutorial||11 weeks||1 per week||1 hour|
Method of Assessment:
|Coursework 1||100||Agent programming practical, 1000 interim report, 4000 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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