Can We Achieve Near-Optimal Self-Play with Minimal Policy Updates?

Multi-agent systems can tackle more complicated tasks than just chess. Image created with DALL-E.

In recent years, reinforcement learning (RL) has proven its worth in training artificially intelligent agents to master tasks as diverse as board games, computer card games, autonomous driving, and adaptive power management. However, many of these settings i…