Chapter 9: Multi-Agent Reinforcement Learning

If there is something more exciting than training a reinforcement learning (RL) agent to exhibit intelligent behavior, it is to train multiple of them to collaborate or compete. Multi-agent RL (MARL) is where you will really feel the potential in artificial intelligence. Many famous RL stories, such as AlphaGo or OpenAI Five, stemmed from MARL, which we introduce you to in this chapter. Of course, there is no free lunch, and MARL comes with lots of challenges along with its opportunities, which we will also explore. At the end of the chapter, we will train a bunch of tic-tac-toe agents through competitive self-play. So, at the end, you will have some companions to play some game against.

This will be a fun chapter, and specifically we will cover the following topics:

• Introducing multi-agent reinforcement learning,
• Exploring the challenges in multi-agent reinforcement learning,
• Training policies in multi-agent settings...