Reinforcement Learning, Part 2: Policy Evaluation and Improvement

From data to decisions: maximizing rewards with policy improvement methods for optimal strategies

Introduction

Reinforcement learning is a domain in machine learning that introduces the concept of an agent who must learn optimal strategies in complex environments. The agent learns from its actions that result in rewards given the environment’s state. Reinforcement learning is a difficult topic and differs significantly from other areas of machine learning. That is why it should only be used when a given problem cannot be …

agent artificial intelligence concept data data science decisions domain environment environments evaluation improvement learn machine machine learning part policy reinforcement reinforcement learning state strategies the environment