An interesting article emerged recently (Kagan, Brett J., et al. “In vitro neurons learn and exhibit sentience when embodied in a simulated game-world.” Neuron (2022).) that teaches brain cells to play pong, but at the same time tests an interesting hypothesis about utilizing the free enrgy principle as a feedback learning mechanism. From the paper:

One proposition for how intelligent behavior may arise in an intelligent system embodied in an environment is the theory of active inference via the free energy principle (FEP) (Friston et al., 2012). The FEP suggests a testable implication that at every spatiotemporal scale, any self-organizing system separate from its environment seeks to minimize its variational free energy (VFE)

The testing from the paper:

To test whether learning reflects a reduction in VFE within BNNs, we used the information entropy of neuronal responses as a proxy for the average surprise (a.k.a. self-information), which is upper-bounded by VFE (see STAR Methods). We predicted a reduction in information entropy during the learning of gameplay. We further predicted an increase in entropy following unpredictable (random) feedback, reflecting and ensuing state of “surprise” (and, implicitly, high VFE), relative to pre-feedback states.