1/ I'm excited to share our new paper, now in @Nature!
Paper: https://t.co/y2KA9wFnoF
PDF: https://t.co/hRGO8s7oo3
Summary 🧵:
We present a new theory of problem simplification to answer an old question in cognitive science and AI:
How do we represent problems when planning?
We hope you can join!
These workshops were organized by a stellar team ✨
@dvgnagy Hanqi Zhou, Shuze Liu, Tracey Mills, @chentoast1 and Zergham Ahmed
For more info and updates, please see our website: https://t.co/sFxJYNYgO0
How do human minds make sense of big, messy problems? 😵💫🌀
How do we distill complexity into something simple enough to solve? 🤔💡
We’ll be tackling these questions (and more!) at two workshops on task representations, abstractions, and construals #CogSci2026#CCN2026 🧵
New book The Laws of Thought is out tomorrow! Just as Algorithms to Live By introduced ideas from computer science through their applications in everyday life, the Laws of Thought introduces ideas from cognitive science and AI through the stories of the people who created them.
New book The Laws of Thought is out tomorrow! Just as Algorithms to Live By introduced ideas from computer science through their applications in everyday life, the Laws of Thought introduces ideas from cognitive science and AI through the stories of the people who created them.
Excited to announce a new book telling the story of mathematical approaches to studying the mind, from the origins of cognitive science to modern AI! The Laws of Thought will be published in February, and is available for pre-order now.
Very excited about this preprint! We used LLMs and a large-scale eye-tracking study to (I think) really nail some questions that psycholinguists have been debating for decades:
Why are some syntactic structures harder to read than others? How much of this difficulty can be explained by predictability? When we go back and reread earlier words in the sentence, how do we choose which words to read?
It was great to work on this project with @wtimkey8 and @byungdoh, Kuan-Jung Huang, @sArehalli, @grushaprasad and Brian Dillon!
🚀 Excited to share a new preprint, accepted as a spotlight at #NeurIPS2025!
Humans are imperfect decision-makers, and autonomous systems should understand how we deviate from idealized rationality
Our paper aims to address this! 👀🧠✨
https://t.co/jOLXBdELTt
a 🧵⤵️
happy to be a part of this work, on how to use IRL to infer and work with more general cognitive priors, nice paper bridging these domains by @mark_ho_, @EugeneVinitsky, and team (thanks @SounakBanerjee, all!), spotlighted in #neurips2025!
I have been a fan of Mark's work for a decade and in this work I finally had an opportunity to collaborate with him and his postdoc @SounakB02298201! In this work I believe we are taking important steps towards bringing computational cognitive science to real-world naturalistic
Finished teaching my first seminar course today! Had tons of fun introducing my students to the rational foundations of human-like cooperation. Now that the course is over, I'm sharing the syllabus more widely!
One reason I’m excited about this work is that it is step towards scaling cognitive models to naturalistic domains, like driving 🚗
This pushes cognitive modeling approaches forward while helping bridge the gap between cognitive science theory and real-world autonomous systems!