[vstuart]

I agree; Karl Friston's work is among the most interesting I have ever read, period. Interestingly, his 2009 paper (https://www.fil.ion.ucl.ac.uk/~karl/The%20free-energy%20prin...) / free-energy principle makes use of reinforcement learning, gradient descent, Markov blankets, Helmholtz machines, and other foundational tenets of modern machine learning ... In that regard, Geoff Hinton (a foundational figure in modern machine learning) overlapped with Friston while Hinton was in England at that point in his career.

[MrQuincle]

Yes, interesting man. I encountered him on a workshop by Bert Kappen on stochastic optimal control. It shows that there are different control strategies for different noise levels separated by phase transitions.

I checked Friston again. He now also has this article: https://www.frontiersin.org/articles/10.3389/fncom.2012.0004...

CLE = Conditional Lyapunov Exponents.

"In short, free energy minimization will tend to produce local CLE that fluctuate at near zero values and exhibit self-organized instability or slowing."

I've to study it more what he means with self-organized instability.

[Agebor]

Oh interesting - thanks for the pointers.