Reinforcement Learning – Short Notes | TechAmbitionX
Reinforcement Learning – Short Notes | TechAmbitionX Reinforcement Learning (RL) – Exam Oriented Short Notes Platform: TechAmbitionX 1. Definition Reinforcement Learning is a type of machine learning in which an agent learns optimal behavior by interacting with an environment and maximizing cumulative reward . 2. Key Components Agent: Learner or decision-maker Environment: External system the agent interacts with State (S): Current situation of the agent Action (A): Possible moves by the agent Reward (R): Feedback from environment Policy (π): Strategy followed by the agent 3. Working of Reinforcement Learning Observe State → Take Action → Receive Reward → Move to New State → Update Policy → Repeat 4. Reward Concept Positive reward → Encourages action Negative reward → Discourages action Goal is to maximize total reward over time ...