Reece Keller
CS+Neuro @cmu.edu PhD Student with Xaq Pitkow and @anayebi.bsky.social working on autonomous embodied AI.
- 1/ I'm excited to share recent results from my first collaboration with the amazing @anayebi.bsky.social and @leokoz8.bsky.social ! We show how autonomous behavior and whole-brain dynamics emerge in embodied agents with intrinsic motivation driven by world models.
- 2/ Model-based intrinsic motivation is a class of exploration methods in RL that leverage predictive world models to generate an intrinsic reward signal. This signal is completely self-supervised and can guide behavior in sparse-reward or reward-free environments.
- 3/ Existing model-based intrinsic motivation algorithms (e.g. learning progress, prediction-error) exhibit non-stationary and saturating reward dynamics, leading to transient behavioral strategies that fail to capture the robust nature of ethological animal behavior.
-
View full thread10/ Animal-like autonomy—flexibly adapting to new environments without supervision—is a key ingredient of general intelligence. Our work shows this hinges on 1) a predictive world model and 2) memory primitives that ground these predictions in ethologically relevant contexts.
