Model-free algorithms are a formidable kind of algorithm that have the ability to learn very complex policies and accomplish objectives in complicated and composite environments. As demonstrated in the latest works by OpenAI (https://openai.com/five/) and DeepMind (https://deepmind.com/blog/article/alphastar-mastering-real-time-strategy-game-starcraft-ii), these algorithms can actually show long-term planning, teamwork, and adaptation to unexpected situations in challenge games such as StarCraft and Dota 2.
Trained agents have been able to beat top professional players. However, the biggest downside is in the huge number of games that need to be played in order to train agents to master these games. In fact, to achieve these results, the algorithms have been scaled massively to let the agents play hundreds of years' worth of games against themselves. But...
