1. Hotline Miami Level Layouts
Artificial Intelligence and Games Development Lab 28/09/2017

2. How the Story Began…
In late 2015, I had the opportunity to teach an elective on Procedural Content Generation at Innopolis University, in its old location in an office building in Kazan, Russia.
Developers, Dennaton Games, has announced that a level design package would be in the second game…
Good suggestion for students for final term projects!
Unfortunately, while the game released - the level editor would not release till 2016, so it was not until the second running of this elective, at the new city of Innopolis, in which I was able to again bring forward a team to the problem of level generation in a commercially successful game.
This is when we join our anti-heros…
Bulat Lutfullin – MSc Student/Code Cracker
Pavel Oreshin – MSc Student/Devious Developer
Joseph Alexander Brown – Professor/Mastermind

3. The Master Plan Understanding how the level editor works
Reverse Engineering
What are the primitive objects
Ensure we have a pathway to play developed levels
Development of Level Layouts
Placement of Objects
Placement of Enemies and Power-ups
Human testing

4. Hotline MIami Based on Neo-Noir stylings Stylistic Neon 1980s
Drive w/ Ryan Gosling
David Lynch storyline
Stylistic Neon 1980s
(Un)forgiving – Rougelike(?)
Instant one hit kills to player
No lives or game overs
Pressing R – Restarts the level from the beginning

5. EA System
Create a randomized population made up of chromosomes, data structures which encode a potential solution
Until <Done>, based on a stopping criteria
Find an objective/fitness score for each member of the population
Select members to act upon using some variation operators
Apply operations on the members
Crossover
Mutations
Replace some members of the population with these children from the variation operators
Keep some members from the previous population in the new population, i.e. elitism/inheritance

6. Representation Rooms are defined as a five-tuple (x,y,l,w,t) where:
x is the starting x-coordinate of a room
y is the starting y-coordinate of a room
l is the length of the room
w is the width of the room
t is the placement type of a room, if it places on-top of (O) or under (U) current rooms.

7. Translation
The chromosome below is translated left to right into a level design with some restrictions.
If a room is not overlapped it is not placed.
Doors are placed at the end at random against connecting walls. The connective graph is implicitly defined by rooms placed.

8. Selection and Variation Operations
Selection was made from the Population of 20 individuals of size 10
Two fittest are crossed multiple times and replace entire population
Crossover: Uniform Order, Swap with probability ½
Mutation: Creates an entirely new chromosome
Very Disruptive, but prevents early convergence seen in the model

9. Fitness Evaluations
Developed a series of Fitness functions in order to define a good level behaviour
Seeking to find the right combination of factors to visually see close packed rooms
Want to have interesting connections
Fitness functions should be reflected in the look and feel of the level
Process similar to that taken by:
Ashlock et al. (2011) examining maze generations with graph properties
Valtchanov and Brown (2012) which examined tiles in a Diablo like game with pre-set assets

10. Findings
95% CI about the mean, with 0E0 as machine 0.

11. Maximize Area

12. Minimize Area

13. Minimize Diameter

14. Corridor Penalty

15. Complex

16. Control over Layout via Fitness
The defined fitness functions allow for priority of what graphical, area, or other features should be in a level
High Control over the generator
The set becomes a series of dials
A weighted sum of effect in the final fitness
Developer can turn these dials to their liking to give off the properties expected

17. Usable!

18. Press R to restart Placement of PCG elements into existing games
IS HARD – greater effort was spent in the reverse engineering than coding the generator – sadly the second is the research issue
Lots of preparation work that needs to be done to incorporate a functional game into a research tool chain
Developers were very kind in answering some of my questions about the files – but communications were limited – the issue is thinking fast v. slow
Academics
Resources: Time
Actions: Slow Think/Planning
Outcome: Publishable Research
Industry
Resources: Money/Manpower
Actions: Quick Think/Result which works
Outcome: Saleable Product

19. How does the Story Begin?
Placement of Enemies/Pickups/Objects
We only have layouts now which look like levels, but levels should be stocked with baddies and fully playable
Human Testing
Really good suggestion from reviewers was to post this to the Steam Workshop
Collaboration?
Want to try your method for hotline and don’t want to reverse engineer files all day; we are now REALLY good at it.

20. Thank you for your attention!