7

The MDP defines the environment (which corresponds to the task that you need to solve), so it defines e.g. the states of the environment, the actions that you can take in those states, the probabilities of transitioning from one state to the other and the probabilities of getting a reward when you take a certain action in a certain state. The policy ...


3

There's some useful information in your description, but that's just a very vague description of how neural networks with sigmoid activation functions are trained. Moreover, there are many other AI systems apart from neural networks (such as support vector machines, expert systems, etc.), which, of course, I cannot exhaustively list here. Is my ...


3

I think you are looking at it from the wrong direction, min-max is just a planning algorithm, decision strategy, in the sense that you are describing other algorithms/methods it does not have a category. For example, you have negamax algorithm which is in a sense the same thing the Monte Carlo Search Tree is to Monte Carlo. Min-max category is game theory ...


2

Aside from the points raised in nbro's answer, I'd like to point out that for a single MDP (a single instance of a "problem"), it may be sensible to study it from perspectives that include no policy at all, or multiple different policies. For instance, if I have an MDP, I may be interested in studying it by looking at various inherent properties of the ...


2

If it is not defined otherwise, testing is the phase where the model is passed with new data instances to derive the score of the test set. It should not be confused with validation set. A validation dataset is a sample of data held back from training your model that is used to give an estimate of model skill while tuning model’s hyperparameters during ...


1

Keeping this taxonomy intact for model-based Dynamic programming algorithms, I would argue that value iteration is a Actor only approach, and policy iteration is a Actor-Critic approach. However, not many people discuss the term Actor-Critic when referring to Policy Iteration. How come? Both policy iteration and value iteration are value-based approaches. ...


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