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Deep Reinforcement Learning (PPO) applied to a Spiderman Swinging Environment
This project forked from b2developer/spidermanppo
Deep Reinforcement Learning (PPO) applied to a Spiderman Swinging Environment
Load the Unity scene to start Press the Spacebar to start the simulation The AI uses compute shaders to speed up matrix calculations, so if you don't have a GPU it will probably cause some issues / significant speed losses. PROJECT SETTINGS fixed timestep = 0.01 - the AI runs 100 times per second (mainly for stability of physics) physics.autosimulation = false - the AI runs the physics BOOTSTRAP (unity object) ---------------------------- the networks are stored in 4 text files: mu, sigma, value and running. mu and sigma store the actor's neural network, while value stores the critic's neural network. Running stores some moving averages that make the training more efficient TESTING - true (shows the AI running), false (actually trains the AI) LOAD_ID - the name of the network you want to load. If it doesn't exist the app will create one FOLDER_PATH - the path of the folder containing your neural networks RUN_ID - the name of the AI, when new training sessions finish, the AI will be saved under this name with it's performance statistics along side it COUNTER - keeps track of the current training session, you'll need to set this manually to the highest number if you start the application multiple times NEXT_CHECKPOINT - milestone for timesteps, after this number is reached the AI is saved CHECKPOINT_INTERVAL - how far apart should automatic saves be? i've included several AI shown in my video that you can load up using the LOAD_ID ---------------------------- PHYSICS MANAGER (unity object) ---------------------------- the simulation is managed by this object MODE - REALTIME (runs at normal speed), FAST (runs as fast as possible) ENVIRONMENTS - a list of all the active environments, you can add more than one if you like STEPS - how many steps does the FAST mode do at a time? ----------------------------
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