module specification

CU6051 - Artificial Intelligence (2019/20)

Module specification Module approved to run in 2019/20
Module title Artificial Intelligence
Module level Honours (06)
Credit rating for module 15
School School of Computing and Digital Media
Total study hours 150
 
45 hours Scheduled learning & teaching activities
105 hours Guided independent study
Assessment components
Type Weighting Qualifying mark Description
Coursework 25%   Documentation
Coursework 75%   Artefact + documentation
Running in 2019/20
Period Campus Day Time Module Leader
Autumn semester North Thursday Afternoon

Module summary

CU6051 Artificial Intelligence
Autumn Semester (15 credit only)
This module provides an introduction to the field of Artificial Intelligence, from its historical context to its current state.  Students will research an aspect of AI and work in teams to design an intelligent system and develop a simple prototype.

The module aims to –
• to build students’ knowledge and understanding of AI and its range of applications;
• to enable students to use their skills and knowledge to design a contemporary intelligent system;
• to develop students’ critical faculties with respect to the ethics and the issues surrounding AI;
• to build skills in software engineering and prototype development

Syllabus

Agents and environments
Reflex, goal-based agents
State machines
Pathfinding
Knowledge-based systems
Adversarial search
Multi-agent environments
Markov models, uncertainty
Natural Language Processing
Robotics
Human augmentation

Unity tutorials – basics, navigation meshes, decision trees, flocking and steering behaviours

 

LO1 - LO4

Balance of independent study and scheduled teaching activity

Students will have the opportunity to engage in discussions and take part in workshops on different topics.  

Combination of
• Lectures for defining concepts, describing methods and discussing alternatives
• Workshops for demonstrating software tools and platforms, configuring working
environments, prototyping solutions, discussing alternatives and acquiring hands-on experience
• Individual coursework for reporting technological research and technical
solutions, comparing design alternatives and personal reflection
• Blended learning through the use of Virtual Learning Environments (VLE) for
setting problem scenarios, providing prepared solutions, submitting assessment
materials and obtaining feedback
• In-class demonstration of AI solutions for evaluation and reflection of
individual practice

Learning outcomes

Upon successful completion of this module students will be able to:
LO1 - Gain knowledge and understanding of artificial intelligence
LO2 - Be able to work effectively in teams to design an intelligent system
LO3 - Demonstrate ability to communicate effectively on the topic of AI
LO4 – Be able to develop and evaluate a simple AI prototype from a brief

Assessment strategy

Students work independently to produce integrated visual representations (maps) of topics covered in class

Students work independently or in teams of two to produce a prototype working application that showcases an artificial intelligence concept, with accompanying technical and contextual documentation.  This is presented to peers.

Feedback will be given regularly in workshops and when students present work to class.

Bibliography

CORE TEXT
Russell and Norvig  (2015) Artificial Intelligence: A modern approach, 3rd Ed. Pearson india. 
ISBN-10: 9789332543515

SUGGESTED READING
Millington and Funge (2009) Artificial Intelligence for Games; CRC Press.
ISBN-10: 0123747317
Matt Buckland (2004) Programming Game AI by Example; Jones and Bartlett Publishers Inc.
ISBN-10: 9781556220784