Game Artificial Intelligence

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Each day in the schedule shows what topics will be covered in class, what readings will be due for that day, and what assignments will be due that day (if applicable). It also notes when assignments will be released to students.

This schedule is subject to change over the semester. Any major changes will be announced in class.

Week 1: Course Overview

In-Class
Course overview, what is a game and what is game AI?
Out
Midterm paper topic and requirements announced

In-Class
What is Game AI? (continued); game design activity
Reading
“Mechanics, Dynamics, and Aesthetics”, Robin Hunicke et al.
Chapter 1, AI Game Engine Programming, Brian Schwab
(graduate only) Chapter 7, Game Design Workshop, Tracy Fullerton
Out
Assignment 1: Pacman vs. Ghosts

In-Class
Game Design Activity; Pathfinding and Search
Reading
Chapter 4 – 4.4, Artificial Intelligence for Games, Ian Millington & John Funge
(graduate only, undergrad recommended) “Flocks, Herds, and Schools: A Distributed Behavioral Model”, Craig Reynolds
(optional) “The AI Systems of Left 4 Dead”, Michael Booth [note that these are just ppt slides, and will require some interpretation] 

In-Class
Understanding Human Behavior
Reading
The “Real World Bad AI” twitter feed [you are encouraged to come up with your own examples and tweet them to the account! the owner has said he'll RT appropriate examples]
"A Scenario-Based Design Method with Photo Diaries and Photo Essays", Kentaro Go [consider participating in such an activity as part of your reflection]
(graduate only) “Grounded Theory in Ethnography” (pp. 21-25), from Constructing Grounded Theory, Kathy Charmaz
Due       
Midterm Paper Draft 1

In-Class:       
Scripting for AI, Finite State Machines
Reading:       
Chapter 5 – 5.3; 5.10, Artificial Intelligence for Games, Ian Millington & John Funge [link goes to all of chapter 5!]

In-Class:       
Goal-Oriented Action Planning
Reading       
“Three States and a Plan: The A.I. of F.E.A.R.”, Jeff Orkin
(graduate only) Chapters 3 & 4, “Plans and Situated Actions”, Lucy Suchman
Due:               
Peer Feedback for Midterm Paper- outline draft

In-Class:       
Models of Player-NPC Communication
Reading:       
Before class, play Façade and Prom Week
The Eliza Effect, excerpt from "Expressive Processing", Noah Wardrip-Fruin
(graduate only) "ELIZA: a computer program for the study of natural language communication between man and machine", Joseph Weizenbaum

In-Class:       
Behavior Trees & Reactive Planning - Guest Lecture from Damian Isla
Reading:       
Chapter 5.4; 5.9, Artificial Intelligence for Games, Ian Millington & John Funge [link goes to all of chapter 5!]
“Introduction to Behavior Trees”, #AltDevBlog, Bjoern Knafla
(graduate only) "A Behavior Language for Story-Based Believable Agents", Michael Mateas and Andrew Stern
Due
Assignment 1: Pacman vs. Ghosts
Out
Assignment 2: Platformer AI Turing Test

In-Class:       
Utility-Based AI - Guest Lecture from Kevin Dill
Reading:
"Design Patterns for the Configuration of Utility-Based AI", Dill et al.
"A Game AI Approach to Control of Autonomous Virtual Characters", Kevin Dill
Due:               
Midterm Paper Second Draft

In-Class:       
What is Procedural Content Generation?
Reading:       
"The Death of the Level Designer", parts one through six, Andrew Doull
"Procedural Content Generation for Games: A Survey", Hendrikx et al.
(graduate only) "What is Procedural Content Generation? Mario on the Borderline", Togelius et al.

In-Class       
Generating Weapons and Props
Due
Peer feedback on midterm paper - draft 2
Reading       
"Automatic Content Generation in the Galactic Arms Race Video Game", Hastings et al.

In-Class
No class this week – AIIDE conference on campus

In-Class:       
No class this week – AIIDE conference on campus

In-Class:       
Grammars for content generation
Reading:
(undergraduates choose one of these, graduates read both)    
"Procedural Modeling of Buildings", Muller et al.
"Launchpad: A Rhythm-Based Level Generator for 2D Platformers", Smith et al.
Due:               
Assignment 2: Platformer AI Turing Test
Out
Assignment 3: Mario Level Generation

Instructor Out Sick

Due
Midterm Paper [deadline extended to October 28, 11:59pm]

In-Class:       
Optimization and Constraints
Reading:       
(undergraduates choose one of these, graduates read both)
"Search-Based Procedural Content Generation: A Taxonomy and Survey", Togelius et al.
"Answer Set Programming for Procedural Content Generation: A Design Space Approach", Smith and Mateas
Out
Final project proposal requirements.

In-Class:       
Game description languages and rule generation
Reading:   
"A Video Game Description Language for Model-Based or Interactive Learning", Tom Schaul
(graduate only) "EGGG: Automated Programming for Game Generation", Jon Orwant

In-Class:       
Guest Lecture: Jeff Orkin, AI lead on F.E.A.R. and creator of The Restaurant Game
Topic: Crowdsourced Game AI
Reading:       
Jeff has suggested several resources, they are all listed below. Several are quite short, and you are not required to read all of them! Please choose at least two that look interesting to you and read before his guest lecture.
"The First Crowd-Designed Video Game Has Frogs, Lasers, and Hats"
"Pixar Vets Unveil a Genre-Bustin iPad Talk Show that Talks Back"
"Labeling Images with a Computer Game", Luis von Ahn and Laura Dabbish
"Story Generation with Crowdsourced Plot Graphs", Boyang Li et al.
"Online Case-Based Plan Adaptation for Real-Time Strategy Games", Sugandh et al.
"Understanding Speech in Interactive Narratives with Crowdsourced Data", Jeff Orkin and Deb Roy
Due:               
Assignment 3: Procedural Content Generation

In-Class:       
Knowledge representation; final project brainstorming
Reading:       
No reading today
Due:               
Final Project Proposal [Due November 10th, 11:59pm]

Important Note: There is no reading response due this week, and the reading assignments are intentionally lighter than usual. You should still do the reading. Take the extra time for your final project proposal.

In-Class:       
AI in the Game Design Process
Reading:       
None required

In-Class:       
Dynamic Difficulty Adjustment
Reading:       
"AI for Dynamic Difficulty Adjustment in Games", Hunicke & Chapman

In-Class:       
AI-Based Game Design
Reading:       
"AI-Based Game Design: Enabling New Playable Experiences", Eladhari et al.

In-Class:       
TBD
Final project: in-class discussion and work time
Reading:       
TBD

In-Class:       
TBD based on class poll
Reading:       
TBD

No class - Happy Thanksgiving!

In-Class:       
Final project live demos