Thanks so much to @rockberta.bsky.social, Yuri Bizzoni, and Kenneth Enevoldsen for inviting me to visit! The Interacting Minds Center is a really cool place: interactingminds.au.dk/events/singl...

main points: interpretation of R^2 as % var explained (& equivalence w/ correlation^2) only applies to linear models fitted w/ least squares & in-sample. Out-of-sample & beyond linear models: there is no lower bound, models can "hallucinate" variance and R^2 is a comparative metric (vs mean model)

Discussion on generalization / limitations / next steps also included in the preprint. Check out both preprint and package, and reach out if you have feedback! 😎

💡 Finally, preview of the results: 1) diversity is great for performance (# and originality or words named) if turn-taking is flexible; 2) turn-taking styles & diversity modulate search dynamics (e.g., exploration/exploitation); 3) individual flexibility interacts with diversity.

Secondly, the mechanics are fairly simple. Agents have word2vec models as semantic memories & take turns in producing word associations based on distance. Diversity is induced by adding noise to the w2v model. Turn-taking is modulated by defining strict or more flexible rules
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✍️ TL;DRs on rationale, methods, and main findings. Firstly, rationale. Manipulating mental representation and interaction structures "in vivo" is hard. W/ ABS, we can control individual, pair, and interaction-level factors, and assess emergent effects on performance and behavior.

The preprint focuses on two things: a) we introduce and present the paradigm, which we share as a 🐍 package (github.com/rbroc/simcat); b) we use it to study the effects of diversity & social interaction (turn-taking) on performance & behavior in a joint verbal fluency task 🧐

looks cool! Thanks a lot for the pointer!