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5 relations: Algorithm, Machine learning, Markov decision process, Q-learning, Reinforcement learning.
Algorithm
In mathematics and computer science, an algorithm is an unambiguous specification of how to solve a class of problems.
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Machine learning
Machine learning is a subset of artificial intelligence in the field of computer science that often uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed.
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Markov decision process
Markov decision processes (MDPs) provide a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker.
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Q-learning
Q-learning is a reinforcement learning technique used in machine learning.
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Reinforcement learning
Reinforcement learning (RL) is an area of machine learning inspired by behaviourist psychology, concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward.
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References
[1] https://en.wikipedia.org/wiki/State–action–reward–state–action
