Reinforcement Learning Basics 1 — Understanding Stochastic Theory Underlying an MDP

Reinforcement Learning Basics 1 — Understanding Stochastic Theory Underlying an MDP

Reinforcement Learning Basics 1 — Understanding Stochastic Theory Underlying an MDP

“Reinforcement learning (RL) is a type of machine learning that enables an agent to learn to achieve a goal in an uncertain environment by taking actions. An important aspect of reinforcement learning is that it evaluates the actions taken rather than instructs by giving correct actions. Each action has a reward associated with it which signals to the agent the success of the action in progressing towards the goal. The agent navigates the environment repetitively learning how to optimize to reach its goal…”

Source: towardsdatascience.com/reinforcement-learning-basics-1-understanding-stochastic-theory-underlying-an-mdp-e770be0665cf