Ti-Fen Pan
@tifenpan.bsky.social
📤 18
📥 11
📝 3
phd student @
https://ccn.studentorg.berkeley.edu/
reposted by
Ti-Fen Pan
Gaia Molinaro
25 days ago
📢 New preprint! How do humans learn from arbitrary, abstract goals? We show that, when goal spaces can be compressed, costly working-memory processes give way to internalized reward functions, enabling efficient goal-dependent reinforcement learning.
@annecollins.bsky.social
arxiv.org/abs/2509.06810
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Reward function compression facilitates goal-dependent reinforcement learning
Reinforcement learning agents learn from rewards, but humans can uniquely assign value to novel, abstract outcomes in a goal-dependent manner. However, this flexibility is cognitively costly, making l...
https://arxiv.org/abs/2509.06810
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New paper out in Behavioral Research Methods! We introduce a simulation-based method using RNNs to infer trial-varying latent variables from computational cognitive models. Link:
doi.org/10.3758/s134...
#ComputationalCognitiveModeling
#SBI
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Latent variable sequence identification for cognitive models with neural network estimators - Behavior Research Methods
Extracting time-varying latent variables from computational cognitive models plays a key role in uncovering the dynamic cognitive processes that drive behaviors. However, existing methods are limited ...
https://doi.org/10.3758/s13428-025-02794-0
about 1 month ago
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