diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..71624debcf1e5654bb69f6ab45ed18e84e4745a2 --- /dev/null +++ b/README.md @@ -0,0 +1,35 @@ +--- +library_name: ml-agents +tags: +- SoccerTwos +- deep-reinforcement-learning +- reinforcement-learning +- ML-Agents-SoccerTwos +--- + + # **poca** Agent playing **SoccerTwos** + This is a trained model of a **poca** agent playing **SoccerTwos** + using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). + + ## Usage (with ML-Agents) + The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/ + + We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: + - A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your + browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction + - A *longer tutorial* to understand how works ML-Agents: + https://huggingface.co/learn/deep-rl-course/unit5/introduction + + ### Resume the training + ```bash + mlagents-learn --run-id= --resume + ``` + + ### Watch your Agent play + You can watch your agent **playing directly in your browser** + + 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity + 2. Step 1: Find your model_id: brettgoehre/poca-SoccerTwosTest + 3. Step 2: Select your *.nn /*.onnx file + 4. 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trainer_type: poca + hyperparameters: + batch_size: 10000 + buffer_size: 50000 + learning_rate: 0.00015 + beta: 0.0025 + epsilon: 0.2 + lambd: 1.0 + num_epoch: 1 + learning_rate_schedule: constant + beta_schedule: constant + epsilon_schedule: constant + checkpoint_interval: 500000 + network_settings: + normalize: false + hidden_units: 512 + num_layers: 3 + vis_encode_type: simple + memory: null + goal_conditioning_type: hyper + deterministic: false + reward_signals: + extrinsic: + gamma: 0.999999 + strength: 1.0 + network_settings: + normalize: false + hidden_units: 128 + num_layers: 2 + vis_encode_type: simple + memory: null + goal_conditioning_type: hyper + deterministic: false + curiosity: + gamma: 0.999999 + strength: 0.0001 + network_settings: + normalize: false + hidden_units: 512 + num_layers: 2 + vis_encode_type: simple + memory: null + goal_conditioning_type: hyper + deterministic: false + learning_rate: 0.00015 + encoding_size: 512 + init_path: null + keep_checkpoints: 5 + even_checkpoints: false + max_steps: 80000000 + time_horizon: 2000 + summary_freq: 10000 + threaded: false + self_play: + save_steps: 200000 + team_change: 50000 + swap_steps: 3000 + window: 50 + play_against_latest_model_ratio: 0.5 + initial_elo: 1200.0 + behavioral_cloning: null +env_settings: + env_path: ./SoccerTwos/SoccerTwos.app + env_args: null + base_port: 5005 + num_envs: 1 + num_areas: 1 + timeout_wait: 60 + seed: -1 + max_lifetime_restarts: 10 + restarts_rate_limit_n: 1 + restarts_rate_limit_period_s: 60 +engine_settings: + width: 84 + height: 84 + quality_level: 5 + time_scale: 20 + target_frame_rate: -1 + capture_frame_rate: 60 + no_graphics: true + no_graphics_monitor: false +environment_parameters: null +checkpoint_settings: + run_id: BrettOvernight + initialize_from: null + load_model: false + resume: true + force: false + train_model: false + inference: false + results_dir: results +torch_settings: + device: null +debug: false diff --git a/run_logs/Player-0.log b/run_logs/Player-0.log new file mode 100644 index 0000000000000000000000000000000000000000..bb8ca236cd2134b5de33491491ca87a8ab80702a --- /dev/null +++ b/run_logs/Player-0.log @@ -0,0 +1,318 @@ +Mono path[0] = '/Users/brettgohre/Desktop/huggingface/ml-agents/SoccerTwos/SoccerTwos.app/Contents/Resources/Data/Managed' +Mono config path = '/Users/brettgohre/Desktop/huggingface/ml-agents/SoccerTwos/SoccerTwos.app/Contents/MonoBleedingEdge/etc' +New input system (experimental) initialized +Initialize engine version: 2021.3.17f1 (3e8111cac19d) +[Subsystems] Discovering subsystems at path /Users/brettgohre/Desktop/huggingface/ml-agents/SoccerTwos/SoccerTwos.app/Contents/Resources/Data/UnitySubsystems +Forcing GfxDevice: Null +GfxDevice: creating device client; threaded=0; jobified=0 +NullGfxDevice: + Version: NULL 1.0 [1.0] + Renderer: Null Device + Vendor: Unity Technologies +Begin MonoManager ReloadAssembly +- Completed reload, in 0.047 seconds +ERROR: Shader Sprites/Default shader is not supported on this GPU (none of subshaders/fallbacks are suitable) +ERROR: Shader Sprites/Mask shader is not supported on this GPU (none of subshaders/fallbacks are suitable) +ERROR: Shader Legacy Shaders/VertexLit shader is not supported on this GPU (none of subshaders/fallbacks are suitable) +WARNING: Shader Unsupported: 'Standard (Specular setup)' - All subshaders removed +WARNING: Shader Did you use #pragma only_renderers and omit this platform? +WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off? +ERROR: Shader Standard (Specular setup) shader is not supported on this GPU (none of subshaders/fallbacks are suitable) +WARNING: Shader Unsupported: 'Standard (Specular setup)' - All subshaders removed +WARNING: Shader Did you use #pragma only_renderers and omit this platform? +WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off? +WARNING: Shader Unsupported: 'Autodesk Interactive' - All 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