Reinforcement learning is pretty much “non-algorithmic”
I’m rather certain I could implement reinforcement learning as an algorithm. In fact, I’m rather certain I have done so already. If I can point to an algorithm and say “look, that’s a damn reinforcement learning algorithm” then I’m not sure how meaningful it can be to call it “non-algorithmic”.
I concede, RL is a prototype example of algorithmic learning problem. The exploration vs exploitation trade-off is something that needs to be addressed by RL algorithms. It is fair then to say that we gain insight into the “trade-off” by recognizing how the algorithms “solve” it.
I’m rather certain I could implement reinforcement learning as an algorithm. In fact, I’m rather certain I have done so already. If I can point to an algorithm and say “look, that’s a damn reinforcement learning algorithm” then I’m not sure how meaningful it can be to call it “non-algorithmic”.
I concede, RL is a prototype example of algorithmic learning problem. The exploration vs exploitation trade-off is something that needs to be addressed by RL algorithms. It is fair then to say that we gain insight into the “trade-off” by recognizing how the algorithms “solve” it.
It is also fair to say there is an abstract concept of ‘trade off’ that is not itself algorithmic.