Does Sleeping on a idea work? Nice to see our work led by the amazing @anikaloewe.bsky.social and @maritpetzka.bsky.social featured together with other studies in the WaPo:

www.washingtonpost.com/wellness/202...

Our preprint www.biorxiv.org/content/10.1...

I think about this a lot. Thanks @behrenstimb.bsky.social for the wonderfully 90s-vibe blog full of wisdom!

users.fmrib.ox.ac.uk/~behrens/Sta...

In the chess example, the player might have learned from past experience that sacrificing one's queen is generally a bad choice. They would then be less likely to consider solutions involving this move, and less likely to make the 'aha' discovery that it is indeed optimal to do so in this case.

This strategy enables efficient decision-making, but can also lead us astray when our past experience isn't informative for the current context.

We suggest that humans and AI often fail on these problems because they both rely on a planning architecture where possible options are generated based on what was successful in the past and these options are then evaluated based on knowledge of the task at hand.

An example of such a problem is a chess puzzle where sacrificing one's queen is necessary to ensure victory a few steps down the line. A novice chess player who understands the rules of chess might never consider this solution, though they would certainly select it if it were proposed to them

my paper with max, @maxkw.bsky.social, tuomas, and @fierycushman.bsky.social out in cognition at long last www.sciencedirect.com/science/arti...

We explain why humans and successful AI planners both fail on a certain kind of problem that we might describe as requiring insight or creativity

I have been doing entirely too much earnest posting about deep things recently, I need to do a proper thread about hippo testicles or something just to keep myself sane.

Oh by the way hippos have migratory testicles.

New preprint 📝 - another fun collaboration with @arikahn.bsky.social, @licezhang.bsky.social, @nathanieldaw.bsky.social, @hartleylabnyu.bsky.social

We ask: Why do children and adults often derive different representations of their environments from the same experiences? 🧠👶🔎

osf.io/preprints/ps...

TLDR: kids are smart

Our results provide an account of how children and adolescents make flexible choices in a changing world, and suggest a need to better understand how diverse learning strategies influence choices across development.

Here, we ask if children can rely on alternative strategies to use structured knowledge in their choices. We show that children use simplified predictive representations like the Successor Representation to efficiently predict the likely outcomes of their choices without multi-step simulation.

One possible reason for this is that using structured knowledge to make decisions often involves mentally simulating multi-step actions and their outcomes, which can be computationally costly and depend on still-developing cognitive processes

psyarxiv.com/y3dzn preprint from the time i spent at @hartleylabnyu.bsky.social 💜 - we were puzzled by past findings suggesting that children learn about the structure of the world, but don't use this knowledge to flexibly guide their decision-making as much as adults do.