the core idea of story sifting: simulation-driven emergent narrative games (e.g. Dwarf Fortress, The Sims, Crusader Kings II) produce massive profusions of simulated events, most of which are relatively uninteresting, & it’s hard to sift through them to find the good bits…
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…but if we could automatically identify sequences of events that make for interesting story building blocks, we could deliberately surface these sequences to the player to ensure they have a storyful play experience overall
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this is what
@xfoml calls “curationist emergent narrative”: we build simulations that generate tons of events, then curate these events to produce stories that highlight specific sequences of interesting events. for more on this, see James’s dissertation:https://twitter.com/xfoml/status/1096463136297832448 …
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one way to curate events is to write lots of “sifting patterns”: parametrized specifications that describe sets of storyful events in relation to one another. e.g. a sifting pattern could match a sequence of events describing a betrayal, or the formation of a love triangle
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a number of existing story sifting systems, including those developed by
@xfoml, use a sifting pattern-based approach. in existing systems, however, sifting patterns have generally been pretty boilerplate-y & complicated to write, creating a content authoring bottleneckPrikaži ovu nit -
our system, Felt, tries to deal with this problem. our key insight: by using a “real” query language (actually a thin layer of syntax sugar over Datalog) to define sifting patterns, we can make our pattern definitions much more concise & easier to write than in previous systemspic.twitter.com/BZWhEDS2Mb
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there’s a lot of other stuff going on in this paper too. we briefly discuss a few case studies of in-development playable experiences that make use of Felt, including Cozy Mystery Construction Kit, which you might remember from the PCG Workshop this year…https://twitter.com/maxkreminski/status/1138602323922395142 …
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…& we’re also excited about how story sifting can be used to implement character subjectivity if incorporated into simulation: characters can run sifting patterns to “tell themselves stories about” past events, & then act based on their subjective interpretations of these eventspic.twitter.com/JeVX1Fu2jz
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but the #1 reason I’m excited about this paper in particular is because it describes a computational system (Felt) that embodies the “main argument” of my current research direction: emergent narrative game design is a creativity support problem!
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this argument runs through almost all of my recent work – especially Generative Games as Storytelling Partners (https://twitter.com/maxkreminski/status/1146468103766736896 …) & Evaluating AI-Based Games Through Retellings (https://twitter.com/maxkreminski/status/1159874248774569984 …) – & Felt as a system is designed around this ethos from the bottom up
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specifically, Felt is designed for use in mixed-initiative contexts, to surface raw story material to the player in a way that helps players assemble stories of their own. rather than generating stories, we aim to provide computational support for story construction
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Felt: A Simple Story Sifter
Cozy Mystery Construction Kit: Prototyping Toward an AI-Assisted Collaborative Storytelling Mystery Game
documenting the design process for my lab’s main project this past year: using AI & PCG to support player creativity in collaborative storytelling
Evaluating AI-Based Games Through Retellings
we propose a new way to evaluate AI-based games via analysis of player-written stories about play experiences, & demonstrate application of our method to three existing games: Stellaris, Civ VI, & Prom Week