Programming for Game Designers 4: Artificial Intelligence
  I: Administrative Information   II: Course Details   III: Topical Outline(s)  Printable Version
Section I: Administrative Information
  Total hours: 42.0
Credit Value: 3.0
Credit Value Notes: N/A
Effective: Winter 2021
Prerequisites: GAME28567
Corequisites: N/A
Equivalents: GAME33921
Pre/Co/Equiv Notes: N/A

Program(s): Bachelor of Game Design
Program Coordinator(s): Jeffrey Pidsadny
Course Leader or Contact: Nicolas Hesler
Version: 20210118_00
Status: Approved (APPR)

Section I Notes: The Program-wide Design Challenge is a week-long assignment that challenges students to work in teams to research, design and propose solutions to a defined game design problem. Similar in spirit to game jams or hackathons, the activity encourages students to propose innovative solutions while applying the lessons they have learned in class. During the design challenge, faculty provide supportive mentorship through scheduled consultations. The activity is typically scheduled for the week after Reading Week. Typically, teams are assigned and composed of students from across multiple years of the program. The details of the activity, including the day-to-day schedule, are defined at the discretion of the Game Design faculty. During the week of the design challenge, students are expected to attend their regularly scheduled Breadth elective courses.

Section II: Course Details

Detailed Description
Creating engaging play through non-player behaviours in video games requires a strong understanding of artificial intelligence (AI) techniques. Students explore and apply a variety of AI techniques in a game engine to meet game design specifications. Through in-class exercises, analyses, lectures and projects, students develop the practical skills necessary to design and implement effective artificial intelligence for video games.

Program Context

Bachelor of Game Design Program Coordinator(s): Jeffrey Pidsadny
Programming for Game Designers 4: Artificial Intelligence is a mandatory course that provides students with practical game programming skills required to create engaging AI opposition for players and believable Non-Player Character (NPC) behaviours in video games. Students apply this knowledge in their subsequent game design and design practice courses. This course is the fourth mandatory course in the programming stream of courses.

Course Critical Performance and Learning Outcomes

  Critical Performance:
By the end of this course, students will have demonstrated the ability to apply artificial intelligence concepts and techniques in various game projects to achieve play experience goals.
Learning Outcomes:

To achieve the critical performance, students will have demonstrated the ability to:

  1. Explain the purpose and characteristics of various artificial intelligence techniques found in games.
  2. Apply various artificial intelligence techniques in a game engine to meet design specifications.
  3. Deconstruct the behaviour and decision-making of non-player characters in an existing game.
  4. Create a model of behaviour and decision-making for a non-player character.
  5. Implement decision-making models and non-player character behaviour using programming techniques and appropriate tools in a game engine.
  6. Create a system of non-player characters whose behaviour is governed by basic artificial intelligence techniques for games.
  7. Plan a game scenario with non-player characters to motivate specific play behaviour.
  8. Implement a game scenario with non-player characters by applying game design principles and appropriate artificial intelligence techniques for games.
  9. Create an audiovisual presentation for an artificial intelligence solution for a game that highlights key findings and clearly demonstrates the principles applied in the project.

Evaluation Plan
Students demonstrate their learning in the following ways:

 Evaluation Plan: IN-CLASS
 Analysis #1: NPC behaviour analysis10.0%
 Project #1: FSM Ecosystem25.0%
 Program-wide Design Challenge5.0%
 Project #2: NPC Design25.0%
 Analysis #2: AI-motivated player behaviour10.0%
 Project #3: NPC Gameplay Scenario25.0%

Evaluation Notes and Academic Missed Work Procedure:
Academic Missed Work Procedure (Late Submission Policy) All assignments are due within 15 minutes of a deadline set by the professor. Assignments submitted after this time, and up to one day late, will receive a 5% grade reduction. Work submitted after this time, and up to three days late, will receive a 10% grade reduction. Work that is more than three days late will not be graded. Re-submission of work might be granted under exceptional circumstances, at the discretion of the professor. A student may request an extension, stating the reason in writing to the professor at least one day before the deadline. An extension may be granted at the discretion of the professor. Missed in-class activities, assignments and presentations are awarded a grade of zero. A student expecting to be absent from a class activity where a grade would be earned must notify the professor in writing at least one day prior to the scheduled date and make arrangements to reschedule. An extension or alternative evaluation arrangements may be granted at the discretion of the professor. As a rule, work is not accepted after the last day of the term. A student may request in writing an extension to submit work after the last day of the term. An extension may be granted at the discretion of the professor.

Provincial Context
The course meets the following Ministry of Colleges and Universities requirements:


Prior Learning Assessment and Recognition
PLAR Contact (if course is PLAR-eligible) - Office of the Registrar
Students may apply to receive credit by demonstrating achievement of the course learning outcomes through previous relevant work/life experience, service, self-study and training on the job. This course is eligible for challenge through the following method(s):

  • Portfolio
  • Other
    Notes:  Portfolio and Demo Reel. Both are required.

Section III: Topical Outline
Some details of this outline may change as a result of circumstances such as weather cancellations, College and student activities, and class timetabling.
Instruction Mode: In-Class
Professor: Nick Falsitta
RequiredTextbookArtificial Intelligence for Games, Millington, Ian, 3rd Edition, 2019

Applicable student group(s): Honours Bachelor of Game Design students.
Course Details:

Module 1: Movement & Decision Making

  • Introduction to Game AI
    • Academic AI and Game AI
  • Movement
  • Decision making models for games
    • Finite State Machines (FSM)
    • States
    • Transitions
    • Rules
    • Events
  • Analysis #1: NPC behaviour analysis (10%)
  • FSM in a Game Engine
    • Project #1: FSM Ecosystem (25%)

Module 2: Sensing, Steering, Pathfinding

  • Approaches to Sensing
  • Approaches to Steering
  • Navigation meshes
    • Project #2: NPC Design (25%)

Program-wide Design Challenge (5%)

Module 3: Modelling NPC Behaviour

  • Game AI and game design
    • Analysis #2: AI-motivated player behaviour (10%)
  • Behavior Trees
    • Project #3: NPC Gameplay Scenario (25%)


Sheridan Policies

All Sheridan policies can be viewed on the Sheridan policy website.

Academic Integrity: The principle of academic integrity requires that all work submitted for evaluation and course credit be the original, unassisted work of the student. Cheating or plagiarism including borrowing, copying, purchasing or collaborating on work, except for group projects arranged and approved by the professor, or otherwise submitting work that is not the student's own, violates this principle and will not be tolerated. Students who have any questions regarding whether or not specific circumstances involve a breach of academic integrity are advised to review the Academic Integrity Policy and procedure and/or discuss them with the professor.

Copyright: A majority of the course lectures and materials provided in class and posted in SLATE are protected by copyright. Use of these materials must comply with the Acceptable Use Policy, Use of Copyright Protected Work Policy and Student Code of Conduct. Students may use, copy and share these materials for learning and/or research purposes provided that the use complies with fair dealing or an exception in the Copyright Act. Permission from the rights holder would be necessary otherwise. Please note that it is prohibited to reproduce and/or post a work that is not your own on third-party commercial websites including but not limited to Course Hero or OneNote. It is also prohibited to reproduce and/or post a work that is not your own or your own work with the intent to assist others in cheating on third-party commercial websites including but not limited to Course Hero or OneNote.

Intellectual Property: Sheridan's Intellectual Property Policy generally applies such that students own their own work. Please be advised that students working with external research and/or industry collaborators may be asked to sign agreements that waive or modify their IP rights. Please refer to Sheridan's IP Policy and Procedure.

Respectful Behaviour: Sheridan is committed to provide a learning environment that supports academic achievement by respecting the dignity, self-esteem and fair treatment of every person engaged in the learning process. Behaviour which is inconsistent with this principle will not be tolerated. Details of Sheridan's policy on Harassment and Discrimination, Academic Integrity and other academic policies are available on the Sheridan policy website.

Accessible Learning: Accessible Learning coordinates academic accommodations for students with disabilities. For more information or to register, please see the Accessible Learning website (Statement added September 2016)

Course Outline Changes: The information contained in this Course Outline including but not limited to faculty and program information and course description is subject to change without notice. Any changes to course curriculum and/or assessment shall adhere to approved Sheridan protocol. Nothing in this Course Outline should be viewed as a representation, offer and/or warranty. Students are responsible for reading the Important Notice and Disclaimer which applies to Programs and Courses.

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