Using Reinforcement Learning for Classfication Pro

Question

Can I use reinforcement learning on classification? Such as human activity recognition? And how?

Answer 1

Short answer: Yes.

Detailed answer: yes but it's an overkill. Reinforcement learning is useful when you don't have labeled dataset to learn the correct policy, so you need to develop correct strategy based on the rewards. This also allows to backpropagate through non-differentiable blocks (which I suppose is not your case). The biggest drawback of reinforcement learning methods is that thay are typically took a VERY large amount of time to converge. So, if you possess labels, it would be a LOT more faster and easier to use regular supervised learning.

Answer 2

There are two types of feedback. One is evaluative that is used in reinforcement learning method and second is instructive that is used in supervised learning mostly used for classification problems.

When supervised learning is used, the weights of the network, for eg neural network, are adjusted based on the information of correct class labels already present with us. So on selecting a wrong class loss increases and weights are adjusted so that for input of that kind, this wrong class is not chosen again.

However in reinforcement learning, the system explores all the possible actions, class labels for various inputs in this case and by evaluating the reward it decides what is right and what is wrong. It may be the case too that until it gets the correct class label it may be giving wrong class name as it is the best possible output it has found till now. So it doesn't make use of the specific knowledge we have about the class labels, hence slows the convergence rate significantly as compared to supervised learning.

You can use reinforcement learning for classification problems but it won't be giving you any added benefit and instead slow down your convergence rate.