Embed Size (px)
Citation preview
understanding our past to improve our future Gillian Smith
PCG TRIVIA GAME let’s play!
What games are these quotes describing? "Exploration is seeing things that no-‐one else has ever seen before.
Every creature ... is unique.” No Man's Sky, 2015
"Computerized solitaire dungeons, each one will be unique (never two
exactly alike).” A Computer Generated Dungeon, 1977
"randomized levels, the relentless onslaught of monsters and events in
a perpetually fresh world” Diablo III, 2012
"throw a monster [at players] that keeps them on their toes, one that
they have never seen before because it is unique." Random Monsters D&D Supplement, 1980
What games are these quotes describing? "Exploration is seeing things that no-‐one else has ever seen before.
Every creature ... is unique.” No Man's Sky, 2015
"Computerized solitaire dungeons, each one will be unique (never two
exactly alike).” A Computer Generated Dungeon, 1977
"randomized levels, the relentless onslaught of monsters and events in
a perpetually fresh world” Diablo III, 2012
"throw a monster [at players] that keeps them on their toes, one that
they have never seen before because it is unique." Random Monsters D&D Supplement, 1980
Motivations for Generating Content
§ Data compression
§ Replayability
§ Personalization
Platformer AI
Competition, 2013
Elite, 1984
Diablo III, 2012
Motivations for Generating Content
§ Data compression
§ Replayability
§ Personalization
Platformer AI
Competition, 2013
Elite, 1984
Diablo III, 2012
We know how to do this!
But… design tools? "Build the whole adventure yourself or ask the computer
to do it for you." "Begin the construction process with as much or little as
you like...” Adventure Construction Set, 1984
"[it creates] a different maze every time it is run and
guarantee only one path through” AMAZIN, 1973
"[generated monsters] created by computer program to
completely eliminate bias and error” Trolls & Trollkin, 1979
Getting stuck in a motivation rut?
Our Motivations and Backgrounds
§ AI: testing AI through games as a testbed § HCI: helping human designers
§ Creativity: modeling (human?) creativity
§ Game industry: solving authoring burden
§ Game design: designing innovative and fun games
§ Making: the joy of making things that make things
HISTORICAL TRAJECTORIES where have we been and where can we go?
Data to Process Intensive
data-‐intensive Robot Unicorn Attack
process-‐intensive Petalz
Deeply Process Intensive PCG
Deeply Process Intensive PCG
§ Drawing inspiration from other sources § Rationalizing decision-‐making
Static to Playable Content
static content Speed Tree
playable content Angelina
Deeply Playable Content
Deeply Playable Content
§ New, themed game mechanics § New game genres
Developer to Player Control
developer control Elite
player control Spore
Players and Beyond
Players and Beyond
§ “Magic crayons” for playable content § Beyond players: communities, observers
Single to Multiple Players
single player Rogue
multiple players Galactic Arms Race
Multi-‐Player, Multi-‐Creator
Multi-‐Player, Multi-‐Creator
§ Content for many players across instances § Collaborative play
Common Aesthetics
§ Discovery
§ Challenge
Common Aesthetics
§ Discovery § Challenge § Fellowship § Sensation § Fantasy § Narrative § Expression § Submission
Summary
§ Process-‐intensive § DePining new genres § Communities of players § Collaborative play § Alternate aesthetics
FUTURE OF PCG DEVELOPMENT best practices for pcg through understanding generator history
Launchpad’s Expressivity
1 level
>75 levels
Linearity
Linearity
Leniency
Leniency
Comparing Generators
Open Questions in Expressivity Analysis
§ What metrics should we use? § Individual levels § Pairwise comparison
§ How do we know metrics are valid?
§ How do we visualize results?
§ How does this apply to user-‐created content?
Expressive Range as a Debugging Tool?
§ Static analysis lets us see results of code changes quickly
§ Gain better understanding of generator capabilities
Uncovering Biases all lengths length 5 length 10 length 15 length 20
all types
regular
random
swing
FUTURE OF PCG-‐BASED GAMES player exploration of historical choices
Co-‐Design of PCG and Game
Launchpad
§ Rhythm-‐based
§ Control type Parameterized
§ Control extent Compositional Experiential
Endless Web
Player explores the Dream to Pind and rescue six dreamers trapped in their nightmares.
Themes: Exploration and Creation
§ Players navigate physical space while exploring generative space
§ Choices lead the player to newly generated terrain with different generation parameters
Guiding the Player
Goal-‐driven exploration of generative space
An Early Prototype…
“Mechanical Experience”
§ Interaction with generator
§ Multiple simultaneous universes unlocked by choice
§ Comparing player histories
§ Comparing “parentage” of evolved content
FUTURE OF PCG DESIGN TOOLS a generator that can learn from its global history
Current PCG Design Tools
§ Single user § Single AI § Static heuristics § Unchanging design knowledge
Collaborative Design
§ Conversation between active participants
§ Participants have different goals and expertise
§ Diversity of experiences
§ Prototype and discuss different ideas
Overriding Human Decisions
§ …but for a good, and well-‐explained, reason! § Early decisions can become less important § (Novice) designers struggle with undoing work they have already done
§ Example: removing a previously agreed-‐upon game mechanic due to a change in the story
Moving Away from Turn-‐Taking
§ Computer can work independently § Computer is no longer purely reactive, must be proactive in conversation
§ Both parties may interrupt each other or pause to think
§ Example: interrupt a designer with a new idea for a level during brainstorming
Negotiating High-‐Level Design Goals
§ Awareness of additional constraints § Present different “opinions” on design § High-‐level understanding leads to better communication
§ Example: properties of a game level based on current level progression
Many Research Angles § Support for multiple designers
§ Learning from its own history § Building up a new pattern library
§ Integrating playtesting § Understand playtest data and improve
§ Building stronger processes § Rationalizing decisions to user § Overriding human decisions
§ Building smarter interfaces § Representing AI “thought” to designer
FUTURE OF PCG? learning from our past
Future Directions
§ Finding new motivations § Extending along multiple dimensions § Experimenting with new aesthetics § Improving development practices § Enabling new experiences § Building smarter tools
Questions?
Thanks!
[email protected] @gillianmsmith
http://www.sokath.com
Looking for a postdoc position?
Want to do a PhD? Talk to me!
