This section showcases a collection of pictures related to Reinforcement Learning, a branch of machine learning. It is an exciting field that deals with the learning of decision-making in an environment to maximize some notion of cumulative reward.
Key Concepts in Reinforcement Learning
- Agent: The decision-making entity in an environment.
- Environment: The environment in which the agent interacts.
- State: The state of the environment at a particular time.
- Action: The action taken by the agent in a particular state.
- Reward: The scalar value indicating the goodness or badness of an action.
Examples of Reinforcement Learning
- Playing video games
- Autonomous driving
- Stock trading
Related Resources
Images
Reinforcement Learning Algorithm
Q-Learning
Deep Q-Network (DQN)