> what the reward / punishment system really equates to
Nothing, and least as far as neural network training goes. This is an extremely poor analogy regarding how neural networks learn.
If you've ever done any kind of physical training and have had a trainer sightly adjust the position of your limbs until what ever activity you're doing feels better, that's a much closer analogy. You're gently searching the space of possible correct positions, guided by an algorithm (your trainer) that knows how to move you towards a more correct solution.
There's nothing analogous to a "reward" or "punishment" when neural networks are learning.
Yeah but even in that case, "reward" is just the thing a NN is trying to predict. The NN itself is not receiving the reward (or any punishment). Instead, it's following gradient signals to improve that estimate of reward, which is then used as a proxy for an optimal policy decision.
> what the reward / punishment system really equates to
Nothing, and least as far as neural network training goes. This is an extremely poor analogy regarding how neural networks learn.
If you've ever done any kind of physical training and have had a trainer sightly adjust the position of your limbs until what ever activity you're doing feels better, that's a much closer analogy. You're gently searching the space of possible correct positions, guided by an algorithm (your trainer) that knows how to move you towards a more correct solution.
There's nothing analogous to a "reward" or "punishment" when neural networks are learning.