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Why I don't like the term "AI"

Content note: I replicate some ableist language in this post for the sake of calling it out as ableist.

In games research, some people take pains to distinguish artificial intelligence from computational intelligence (Wikipedia summary), with the primary issue being that AI cares more about replicating human behavior, while CI is "human-behavior-inspired" approaches to solving concrete problems. I don't strongly identify with one of these sub-areas more than the other; the extent to which I hold an opinion is mainly that I find the distinction a bit silly, given that the practical effects seem mainly to be that there are two conferences (CIG and AIIDE) that attract the same people, and a journal (TCIAIG - Transactions on Computational Intelligence and Artificial Intelligence in Games) that seems to resolve the problem by replacing instances of "AI" with "CI/AI."

I have a vague, un-citeable memory of hearing another argument from people who dislike the…
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Paper and Game of the Week

This past week I attended (and co-chaired, organized a workshop for, and presented at) the International Conference on Interactive Digital Storytelling (ICIDS). In celebration of a successful ICIDS, I'll share a Paper and Game of the Week each of which I discovered during it.

Paper of the Week: "Using BDI to Model Players Behaviour in an Interactive Fiction Game" By Jessica Rivera-Villicana, Fabio Zambetta, James Harland, and Marsha Berry; available for download on ResearchGate. Disclaimer: I attended the talk about this paper, but have only skimmed the text of the paper itself.
Player modeling is a sub-area of game AI concerned with representing and tracking players' mental states and experiences while playing a game. This is the first paper I've seen addressing the problem in an interactive narrative context. BDI stands for Belief, Desire, and Intention, a philosophical framework for agent modeling (from 1987) that supposes all actions are driven by those three …

Paper and Game of the Week

Paper of the Week: Imaginative Recall with Story Intention GraphsBy Sarah Harmon and Arnav Jhala. Bias disclaimer: both Sarah and Arnav are folks I've worked with and consider colleagues.
Imaginative recall is the process of generalizing and extrapolating previously-seen narrative examples to create new ones. Harmon and Jhala present an automated system for carrying out this process based on a narrative representation scheme called story intention graphs (SIGs).
This paper was a bit hard for me to tease apart initially because there are really two things going on:The system of imaginative recall originally embodied by the Minstrel system, later adapted to the modern rewrite Skald, which uses case-based reasoningThe translation between Skald story representation and SIGs (1) is largely prior work, but lays the groundwork and motivation for their project. Ultimately they are interested in the problem of carrying out processes on narratives such as adaptation, transformation, and mea…

Paper and game of the week

I'm going to try to loosen the ol' blogging joints a bit by experimenting with a weekly feature: a Paper and Game of the Week, posted every Friday morning. My goal will be to keep a record of recent research inspirations in the hopes of exposing interesting gems to others, and providing better context for my own work. I will preemptively establish the expectation that the paper and game of the week may not *literally* be a paper and a game; the objective is more like "something CS-academia-centered" and "something creativity/arts-movement centered," which for me in recent weeks has mostly meant papers and games, but at other times has included talks, interactive essays, plays, art exhibits, and weird internet art.

So without further ado:

Paper of the WeekCommonsense Interpretation of Triangle Behavior by Andrew S. Gordon (not Andrew D. Gordon, although his papers might easily feature on this blog too).
This paper is a formalization of the reasoning that psy…

Two talks: an introduction to the POEM lab; a survey paper on story generation

Principles of Expressive Machines Last week I gave a presentation to the first-year computer science grad student seminar on my research, AKA an introduction to the "Principles of Expressive Machines" (POEM) lab, because I am looking for students. This talk was my first attempt to organize my future research plans into something vaguely coherent and forward-looking (in more depth than my job talk described), so I thought I'd share the results of my efforts. Here are the slides:

In the talk, I outline three research agendas:

Narrative knowledge representation and generationTools for game and interactive fiction designSocial multi-agent system modeling The slides are not particularly verbose, but there should be enough in them to grant a sense of what I'm interested in.
Story Generation Survey This semester, I'm teaching a course on Generative Methods, i.e. algorithms for producing creative artifacts -- such as stories. For the most part, students have been presen…

Augmenting reality without augmenting vision

A common narrative that people tell about virtual and augmented reality (VR and AR) goes something like this: "VR means total immersion in an environment, allowing a game designer to involve you directly in their completely hand-fabricated version of reality. It does this by completely supplanting your field of vision with a simulated 3D environment. AR, on the other hand, only supplants part of your field of vision, allowing overlays of simulated objects and information atop what is otherwise seen normally in the world."

The attentive reader will notice that one sense in particular was heavily emphasized in this explanation: vision. It seems like many people almost take it as a given that supplanting or augmenting reality means changing what we see in a very literal way, and sometimes this idea becomes almost a magic bullet, as though manipulating vision is all it takes to create compelling experiences, as if a more convincing simulation of vision is the main missing piece …

Arguing for your research

Everything from paper abstracts to grant proposals to fellowship applications, at every level from an undergraduate independent study to a full grant proposal as a faculty member, requires one key task: convincing the reader that your research project is any good. Usually "good" more specifically means: does it solve an important problem? Does it address an important issue? Does it explore important unexplored territory? And, if you haven't done it yet, do you have the right tools to solve/address/explore it?

In general, I'm not a huge believer in "formulaic" writing -- the idea that every body of writing ought to be formatted the same way for best results. Especially in creative domains, so much power can be wielded in breaking traditional structures. But for scientific writing, especially project proposals or article submissions, I do find that it really helps to not have to think about how to structure something and instead just plop down a default outli…