Reinforcement learning (RL) is a branch of machine learning that addresses problems where there is no explicit training data. Q-learning is an algorithm that can be used to solve some types of RL ...

We propose for risk-sensitive control of finite Markov chains a counterpart of the popular Q-learning algorithm for classical Markov decision processes. The algorithm is shown to converge with ...

In contrast to the Q-learning algorithm in which nonregular inference is involved, we show that, under assumptions adopted in this paper, the proposed smoothed Q-learning estimator is asymptotically ...

Since the news of Q* broke, many researchers outside OpenAI have speculated about whether the name is a reference to other existing techniques within the field, such as Q-learning, a technique for ...

A special category of algorithms, machine learning algorithms, try to “learn” based on a set of past decision-making examples.