How does a # ReinforcementLearning agent decide what to do? Part 3 of my RL series tackles this by defining policies, MDPs and trajectories. We'll keep building
This article explains how reinforcement learning agents make decisions by defining key concepts. It covers policies, Markov Decision Processes (MDPs), and trajectories. The series aims to build understanding towards the Proximal Policy Optimization (PPO) algorithm. AI
IMPACT Explains fundamental concepts in reinforcement learning, crucial for understanding agent behavior and advanced algorithms.