Reinforcement learning has gained popularity among developers who wish to build game-playing AIs for various reasons – to simply check the capabilities of the AI, to build a training agent that helps professionals improve their game, and so on. From a researcher's point of view, games offer the best testing environment for reinforcement learning agents that can make decisions based on experience and learn to survive/achieve in any given environment. This is due to the fact that games can be designed with simple and precise rules, where the reaction of the environment to a certain action can be accurately predicted. This makes it easier to evaluate the performance of the reinforcement learning agents, and thereby facilitate a good training ground for the AI. With the breakthroughs in game-playing AIs taken into consideration, it...
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