Max Kreminski

Me in my workspace.

Assistant Professor, Computer Science and Engineering
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. In September 2022, I’m starting as an Assistant Professor of Computer Science and Engineering at Santa Clara University.

The central goals of my research are to lower barriers to entry in creative fields and promote reflective practices in creation. To this end, I frequently approach creativity as a form of play, employing methods from games research and design to better understand and support creation as an intrinsically rewarding process. I sometimes call myself a “methodological omnivore”, and I’ll use tools from pretty much any field or discipline to further my aims. However, I’m especially fond of logic programming approaches to computational creativity; grounded theory and ethnographic methods for understanding user experience; and computational caricature as a way to probe the space of possible creativity support tools.

Here’s a complete list of my papers. 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.
📝 Papers: AIIDE 2022
✨ Collaborators: Melanie Dickinson
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.
📝 Papers: FDG 2020, ELO 2020, PCG 2019, AIIDE 2020, ICCC 2021
✨ Collaborators: Melanie Dickinson
Partial example of a Felt sifting pattern that matches a sequence of events involving two impulsive betrayals.
Felt is a simple story sifting and simulation engine for emergent narrative play experiences. It provides narrative system developers with tools for defining story sifting patterns that match narratively potent sequences of events, and for building simulations in which characters make use of story sifting to reason about the world.
📝 Papers: ICIDS 2019
🗞️ Press: The Verge
✨ Collaborators: Melanie Dickinson
Screenshot of Synthesifter’s user interface, synthesizing a sifting pattern that matches a sequence of two romantic failures followed by a romantic success.
Synthesifter is a graphical authoring tool that uses inductive logic programming to help users write story sifting patterns. Users specify concrete positive and negative examples of the kinds of microstories they want to match, and the system interactively synthesizes a Felt sifting pattern that meets their requirements.
📝 Papers: INT 2020
Visualization of a pool of partial Winnow sifting pattern matches evolving as new events take place.
Winnow is a human-friendly domain-specific language for writing story sifting patterns. It provides unique affordances for incremental story sifting, enabling the computer to detect emergent microstories while they’re still playing out.
📝 Papers: AIIDE 2021
✨ Collaborators: Melanie Dickinson
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.
📝 Papers: FDG 2019 (best paper honorable mention), ICIDS 2018
✨ Collaborators: Jacob Garbe
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.
📝 Papers: ICIDS 2021a (best short paper nominee), ICIDS 2021b (best short paper nominee), AIIDE 2019, UX of AI 2019

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.
📝 Papers: AIIDE 2020, ICCC 2021
✨ Collaborators: Melanie Dickinson
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.
📝 Papers: CoG 2021, FDG 2021 (best game or demo)
✨ Collaborators: Tamara Duplantis, Isaac Karth

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.
📝 Papers: AIIDE 2021
🗞️ Press: New Scientist, The Next Web, Dicebreaker
✨ Contributors: Isaac Karth
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.
📝 Papers: FDG 2020 (exceptional paper), CHI 2021, CHI 2020, book chapter, Frontiers in VR
✨ Collaborators: Edward Melcer, Katy Grasse, Nick Junius, many others
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.
📝 Papers: HAI-GEN 2022, ICCC 2021, PCG 2019
🗣️ Talks: !!Con West 2019, Computational Poetry Workshop 2019
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.
📝 Papers: PCG 2018