Max Kreminski

Max Kreminski

Research Scientist, Midjourney
Assistant Professor, Santa Clara University

Pronouns: they/them

About

I’m a researcher in artificial intelligence, human-computer interaction, and creativity. I primarily design and develop AI-based creativity support tools to assist human designers and artists, particularly in the domains of storytelling, poetry, and game design. As an interdisciplinary scholar with a background in technical games research, I’ve also worked on a wide variety of topics related to interactive narrative and digital games.

Currently, I’m a Research Scientist at Midjourney, where I lead the storytelling tools research lab. I’m also an Assistant Professor of Computer Science and Engineering at Santa Clara University (on leave for the 2023-2024 school year). I hold a Ph.D. in Computational Media from the University of California, Santa Cruz, where I was a member of the Expressive Intelligence Studio. In the past, I’ve also been a resident at Stochastic Labs; a consultant at various game industry and tech companies; and a researcher in several labs, most notably the Mobile & Environmental Media Lab, at the University of Southern California.

Here’s a complete list of my papers (current count: 57; awards and nominations: 8). You can also check out my full CV for links to many of my talks and other scholarly output.

Intelligent narrative technologies

Screenshot of several storytelling goals, each representing a different plot thread, in in the Loose Ends user interface.
Loose Ends is an AI-based narrative instrument that can be played to produce narrative, much like a musical instrument can be played to produce music. It aims to help players interleave multiple parallel plot threads into an effective high-level plot structure that satisfies player-specified storytelling goals.
System diagram of Why Are We Like This?, showing how the system suggests what should happen next in response to player actions.
Why Are We Like This? is an AI-augmented collaborative storytelling game. Two players write a story in a pastiche of the cozy mystery genre, with support from a simulation-based AI system that suggests what might happen next based on both character and authorial goals.
Partial example of a Felt sifting pattern that matches a sequence of events involving two impulsive betrayals.
Story sifters are computational recognizers of potentially compelling story structures. I’ve worked to frame story sifting as logic programming (Felt); developed AI-based tools that make logical sifters easier to build (Synthesifter); and enabled sifters to reason about possible future events (Winnow) and prioritize unexpected stories (StU).
System diagram of StoryAssembler, showing how execution co-routines between a forward state-space planner and hierarchical task network planner.
StoryAssembler is an interactive narrative system that assembles choice-based stories on the fly from a library of author-provided story fragments, using planning to ensure that every story it produces meets a set of author-specified requirements.
Partial screenshot of codebook that notes dimensions of variation between Civilization VI and Stellaris retellings, from the AIIDE 2019 paper linked below.
Retellings studies are a series of investigations into the stories that players tell about their experiences in games, especially simulation-driven emergent narrative games. This work helps us better understand how to provide computational support for human storytelling practices.

Computational support for game design

Screenshot of the Germinate user interface, showing a design intent on the left and a generated game on the right.
Germinate is a mixed-initiative casual creator for rhetorical game design, built on the Gemini game generator. It generates games based on a user-provided design intent, then provides users with support in exploring the resulting design space and refining their intent based on the generated games.
System diagram of a single generated Game Boy RPG.
GBS is a genre-specific game description language for Game Boy RPGs, extracted from the GB Studio game creation tool. We’re using it as a shared language between human designers and computational systems to build an ecosystem of game design support tools that better understand games as an expressive medium.

Other selected projects

Screenshot of the Blabrecs AI testing the nonsense word “torbible” and saying “looks good to me!”
Blabrecs is a rules modification for the wordgame Scrabble that forbids players from using actual English dictionary words. Instead, players may only use nonsense words that sound like English to an AI trained on the dictionary.
Screenshot of an Academical scene in which an aging hippie professor discusses an ethical dilemma with a grad student.
Academical is an interactive narrative game that uses roleplaying to train new researchers in responsible conduct of research. Our user studies have found that Academical is better than existing RCR training materials at engaging users, teaching some RCR topics, and promoting moral reasoning, without falling behind in other areas.
A two-line poem created using Redactionist: “the mission is the infinite variability / that poetry can speak”.
Redactionist is an AI-based tool that helps you create poetry by erasing words from a source text. It builds on my earlier work in this direction: a browser bookmarklet that can turn any arbitrary webpage into blackout poetry.
Screenshot of Epitaph, showing a procedurally generated alien civilization called the Gep.
Epitaph is a procedural narrative idlegame about existential risks and the death of civilizations. Bennett Foddy (the creator of QWOP) considers it “one of the great web games”. It was the precursor to my academic work on gardening games, which use procedural content generation to support gameplay experiences of caretaking rather than extraction.