Search Results for author:
Found 5 papers, 2 papers with code
Knitting a Markov blanket is hard when you are out-of-equilibrium: two examples in canonical nonequilibrium models
Bayesian theories of biological and brain function speculate that Markov blankets (a conditional independence separating a system from external states) play a key role for facilitating inference-like behaviour in living systems.
How particular is the physics of the free energy principle?
We discover that two requirements of the FEP -- the Markov blanket condition (i. e. a statistical boundary precluding direct coupling between internal and external states) and stringent restrictions on its solenoidal flows (i. e. tendencies driving a system out of equilibrium) -- are only valid for a very narrow space of parameters.
Adaptation to criticality through organizational invariance in embodied agents
In order to explore how criticality might emerge from general adaptive mechanisms, we propose a simple learning rule that maintains an internal organizational structure from a specific family of systems at criticality.
Criticality as It Could Be: organizational invariance as self-organized criticality in embodied agents
This paper outlines a methodological approach for designing adaptive agents driving themselves near points of criticality.
Learning Criticality in an Embodied Boltzmann Machine
We test and corroborate the model implementing an embodied agent in the mountain car benchmark, controlled by a Boltzmann Machine that adjust its weights according to the model.
