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PyTorch Implementation for a Reinforcement Learning Agent (DQN) capable of playing several DOOM Scenarios

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ElFosco/DOOM-RL

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DOOM&RL - ViZDoom + DQN

The scope of the project is to develop a DQN agent, capable of playing different scenarios of the game DOOM. The computed models are able to complete the basic scenario and the defend the center level with satisfactory results.

How to run it?

Simply runs the main files, each of them is associated to a scenario and a technique, inside each of them there's a flag called case, switch it between 'training' and 'testing' based on what you want.

Final results - BASIC

Final results - DEFEND THE CENTER

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PyTorch Implementation for a Reinforcement Learning Agent (DQN) capable of playing several DOOM Scenarios

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