Predictive coding characterizes adaptive behavior as a dynamic balance between internally generated predictions and external sensory evidence, yet how an embodied cognitive system can regulate this balance online during ongoing interaction remains poorly understood. This study proposes a predictive-coding-based mechani...
Henrique Oyama, Hiroki Sawada, Jun Tani· 0 citations
The Predictive-Coding-inspired Variational Recurrent Neural Network is extended to continuously adapt its synaptic weights and Free-Energy-Gated Plasticity (FEGP) is proposed, which regulates the effective learning rate according to variational free energy.
A mechanism-by-mechanism transition to the recurrent behavior-cloning baseline shows that replacing the predictive pathway with direct observation input produces the largest single performance drop, accounting for approximately $70\% of the endpoint gap.
Results show that a sub-million-parameter recurrent generative policy can achieve strong performance on modern language-conditioned manipulation benchmarks while providing an explicit mechanism for prediction-error-driven online state correction.
Hiroki Sawada, Shunichi Kasahara· 0 citations
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