Evolving an agent to play the Frostbite Atari game using deep neuroevolution

Recently, classic Atari games were encapsulated by the Atari Learning Environment (ALE) to become a benchmark for testing different implementations of RL algorithms. Algorithms that are tested against the ALE are required to read the game state from the pixels of the game screen and devise a sophisticated control logic that allows the agent to win the game. Thus, the task of the algorithm is to evolve an understanding of the game situation in terms of the game character and its adversaries. Also, the algorithm needs to understand the reward signal that's received from the game screen in the form of the final game score at the end of a single game run.

The Frostbite Atari game

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