In this module, students will focus on the challenging art of designing Artificial Intelligence for a given problem domain. Through scripting complex custom entities, students pit their developed AIs against a series of challenging scenarios included competitive arena-based combat situations.

Students will learn the practical techniques necessary to script complex task-solving AIs within both a commercial and a proprietary engine environment. Topics include:

- Utility
- Finite State Machines and behaviour trees
- Autonomous agents + goal-based agents
- Individual and group steering behaviours
- Collision avoidance
- Pathing and optimisation
- Perceptual modelling
- Decision making
- Inter-agent communication for team AI

1 x 2 hour interactive lecture per week.

Unity Game Engine

Barrera, R. et al. (2015), Unity AI Game Programming (2nd Edition), Packt Publishing
Buckland, M. (2004), Programming Game AI by Example, Wordware Publishing
Kirby, N. (2010), Introduction to Game AI, Delmar
Mark, D. (2009), Behavioural Mathematics for Game AI, Cengage Learning PTR
Millington, I. (2009), Artificial Intelligence for Games, Morgan Kaufmann
Rabin, S. (2015), Game AI Pro 2, A K Peters/CRC Press

1. DEMONSTRATE AN UNDERSTANDING OF TECHNIQUES REQUIRED TO DESIGN AND DEVELOP PRACTICAL ARTIFICIAL INTELLIGENCE USING HIGH LEVEL LANGUAGES.
[Knowledge and Understanding]

2. DEFINE AND REFINE FUNCTIONAL PROGRAMMING CONSTRUCTS REQUIRED TO MEET THE CHALLENGES OF THE ORIGINAL GAME CONCEPT
[Problem Solving]

3. REFLECT UPON THE EFFECTIVENESS OF INDIVIDUAL AND INDUSTRY STANDARD AI TECHNIQUES IN ORDER TO IMPROVE THE CAPABILITY OF DEVELOPED AUTONOMOUS AGENTS.
[Reflection]

4. APPLY KNOWLEDGE AND UNDERSTANDING OF ARTIFICIAL INTELLIGENCE IN ORDER TO PRODUCE FUNCTIONAL AUTONOMOUS AGENTS WITHIN A GAME.
[Application]

A set of AI scripts and associated assets to control a set of multiple agents required to perform a complex tactical challenge. (Learning Outcomes 1, 2, 3 and 4) 50% weighting

A set of AI scripts and associated assets to control a custom set of multiple agents required to perform in a tactical challenge against student-scripted agents. (Learning Outcomes 1, 2, 3 and 4) 50% weighting

Students will focus on the challenging art of designing and implementing Artificial Intelligence systems. Through scripting complex custom entities, students pit their developed AIs against a series of challenging scenarios including competitive arena-based combat and multi-agent tasks.