Syllabus - Artificial Intelligence in Gaming (AL702(A))

CSE

Artificial Intelligence in Gaming (AL702(A))

VII

Unit I

Introduction

Introduction to Game AI, kind of AI used in game development, model of game AI, AI engine structure.

Unit II

Movement Algorithms and Steering Behaviour

Kinematic movement algorithms, problems related to the steering behaviour of objects and solutions. Coordinated Movement and Motor Control. This unit discusses the concepts related to coordinated movements and motor control.

Unit III

Pathfinding

Basic Path finding Algorithms in game development, Path finding for complex solutions

Unit IV

Decision-Making and Uncertainty

Decision trees and state machines for game development, models for implementing knowledge uncertainty, such as fuzzy logic and Markov systems.

Unit V

Introduction to Learning Mechanisms

Board game theory and discusses the implementation of some key algorithms, such as minimax and negamax, Random Number Generation and Minimaxing, algorithms for implementing action prediction, decision learning and reinforcement learning.

Course Objective

The students should be able to understand and use AI techniques for generating efficient, intelligent behavior in games. Additional attention is to be given to AI algorithms for improving game play experience.

Course Outcome

After completion of course, students would be able to: 1. Understand identify tasks that can be tackled using AI techniques. 2. Apply appropriate AI technique for the problem under investigation. 3. Create efficient and robust AI algorithms for game tasks. 4. Apply learning mechanisms to gaming problems.

Practicals

Reference Books

  • https://www.athabascau.ca/syllabi/comp/comp452.php

  • https://www.udemy.com/course/artificial-intelligence-for-simple-games

  • Artificial Intelligence for Games, Ian Millington and John Funge, CRC Press; 2nd edition, 2009.

  • Artificial Intelligence and Games, Georgios N. Yannakakis and Julian Togelius, Springer International Publishing, 2018.