Ti-Fen Pan
@tifenpan.bsky.social
phd student @ https://ccn.studentorg.berkeley.edu/
Reposted by Ti-Fen Pan
📢 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
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
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...
arxiv.org
September 9, 2025 at 1:58 AM
📢 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
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
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
Link: doi.org/10.3758/s134...
#ComputationalCognitiveModeling #SBI
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 ...
doi.org
August 29, 2025 at 9:04 PM
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
Link: doi.org/10.3758/s134...
#ComputationalCognitiveModeling #SBI