[outlace]

It looks like the gel “learns” to get better at the game because if it correctly positions the Pong paddle over time then the dynamics of stimulation become predictable rather than random. since the system tries to naturally minimize its free energy, it will eventually start to model the ball dynamics enough to better control the paddle, all making the input dynamics more predictable and thus minimizing the energy of the system.

[amelius]

> making the input dynamics more predictable and thus minimizing the energy of the system.

How does this follow?

[techjamie]

The traditional way that you train a biological network like this is that you give it stimulations based on what the game is doing and you give it an ability to control the game. But when something bad happens it's given a lot of random stimulation that it doesn't understand. So the biological network tries to minimize the amount of random stimulation it gets and it learns to play the game better because the stimulation is consistent and predictable.

I didn't go into the paper to see if that's exactly what they're doing, and I'm no expert. But from what I've read before, that's how this usually works, and I'm sure they're doing something similar to that.

[scilaaverkie]

Love this point. Willingness to spend less energy = need to find predictable patterns