Multi-Agent Actor-Critic for Mixed cooperative-competitive environments
Introduction Multi-Agent Actor-Critic methods have emerged as a powerful extension of Reinforcement Learning (RL), which has achieved remarkable success in […]
December 2025
Distributed Distributional Actor–Critic (D4PG): A Deep Dive into Modern Reinforcement Learning
Introduction Over the past ten years, Reinforcement Learning (RL) has advanced quickly. D4PG have witnessed notable advancements in the way
Trust Region Policy Optimization with Value Function Critic
Introduction Reinforcement learning has rapidly evolved in the last decade, but one challenge remains constant: how to update a policy
Proximal Policy Optimization (PPO): A Powerful Actor–Critic Reinforcement Learning Algorithm
One of the most popular algorithms for solving Reinforcement Learning (RL) problems is Proximal Policy Optimization (PPO). John Schuman, an
