This is the third of several posts about James Ryan’s dissertation, Curating Simulated Storyworlds. We are now reading chapters 6 and following, in which Ryan describes his own projects in the curated emergent narrative space.

After the first five chapters, this piece becomes considerably more narrative in its own structure: Ryan is (consciously) telling the story of his own artistic development and practice, and the particular works to which it gave rise.

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This is the second of several posts about James Ryan’s dissertation, Curating Simulated Storyworlds. The previous post looked at chapters 1-3, which set out the concept of the dissertation and documented the pleasures of emergent narrative.

Here I read Chapter 4, concerned with the pain of emergent narrative, including critiques from other scholars and projects in emergent narrative that have failed; and Chapter 5, in which he presents his argument for curationist emergent narrative.

The major issues Ryan identifies with simulations are:

Boringness. Some simulations are simulating events that aren’t that engaging, and therefore they will never have the range to compel readers. (Something I was wondering about while reading chapters 1-3.)

Granularity extremes. The system is operating on either too large or too small a scale. As an example, Ryan showcases the system that controls how drinks may be taken in the Saga II story generation system, with an arguably excessive focus on moving objects from hand to hand.

• As a side note: this is a granularity of state that most text adventure games wouldn’t bother with. There are some exceptions, though a few of the most granular works I know of were also never finished: for many years NK Guy worked on a game code-named Hamsterworld, which attended to player clothes and body parts (and many other systems) with great precision; of Gunther Schmidl’s And the Waves Choke the Wind, only a first few scenes were ever released. TADS 3’s library supports more in this range than any other text adventure world model I’m aware of, and handles some of the related challenges around making small actions implicit when they aren’t individually very interesting, so that at its best, the granularity of the world model becomes invisible except when there is something down in those details that really does interfere in the player’s intended action, at which point the consequence is reported. Return to Ditch Day remains one of the best examples of this kind of work, and Eric Eve’s work is also exemplary here.

Lack of modularity. The idea here is that elements of the simulation must be small and reusable; otherwise, it isn’t possible to recombine them in interesting ways. To illustrate this issue, Ryan looks at Sheldon Klein’s murder mystery generator, an example I haven’t seen written up particularly often (though perhaps I’ve been looking in the wrong places).

Lack of abstraction. Here, Ryan argues for the value of simulators that can cast different characters in different spaces and situations, rather than retelling (possibly different) stories about the same set of characters and events, since if we have a large number of stories about different characters, the appeal of the vast and the appeal of the ephemeral are preserved. (These are key features of the aesthetic of emergent narrative, as Ryan lays these out in earlier chapters.)

I am not sure what I think about this one. I will grant that the repetition of the same characters can give a kind of sameyness to story generators — though some systems, from Fallen London to Rafael Pérez y Pérez‘ Mexica, refer to characters by title or function in order to avoid the concrete effect of granting them a name.

Modeling gaps. This refers to places where it seems the simulation ought to cover some possibility or set of actions, based on what else is modeled, but for some reason certain elements are omitted.

Causality issues. Here Ryan describes how simulation causality can be too diffuse to make for good storytelling, especially in systems that rely on utility scoring where many different aspects of world state could all be considered to partially explain a particular outcome. (He gives a detailed example based on trying to interpret consequence in Prom Week, which is especially valuable here.) Though I’ve encountered this phenomenon, I haven’t seen the problem labeled or analyzed in depth before.

The solution Ryan proposes — contingent unlocking, where some events explicitly are made possibly by a finite set of prior conditions, and causal bookkeeping, where the system somewhere records how a particular outcome has been made available — will apparently come back in later chapters when he talks about his own work.

It’s a method we also used to some degree in Versu, where characters could record a string that represented why they’d adopted a particular attitude towards the player; and for that matter I use it lightly in my Choice of Games work in progress, which is not a simulation of the kind Ryan is talking about at all, but I still find it useful for the sake of later callbacks to be able to recall, say, the worst thing one character has ever done to another.

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After these, Ryan next identifies pains of curation, and this is where the gloves come off.

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