Reinforcement Learning
ml-agents
ONNX
deep-reinforcement-learning
Pyramids
ML-Agents-Pyramids
Eval Results (legacy)
Instructions to use rondahahda/ppo-Pyramids with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use rondahahda/ppo-Pyramids with ml-agents:
mlagents-load-from-hf --repo-id="rondahahda/ppo-Pyramids" --local-dir="./downloads"
- Notebooks
- Google Colab
- Kaggle
File size: 2,779 Bytes
9e3ffe2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 | {
"default_settings": null,
"behaviors": {
"Pyramids": {
"trainer_type": "ppo",
"hyperparameters": {
"batch_size": 128,
"buffer_size": 2048,
"learning_rate": 0.0003,
"beta": 0.01,
"epsilon": 0.2,
"lambd": 0.95,
"num_epoch": 3,
"shared_critic": false,
"learning_rate_schedule": "linear",
"beta_schedule": "linear",
"epsilon_schedule": "linear"
},
"checkpoint_interval": 500000,
"network_settings": {
"normalize": false,
"hidden_units": 512,
"num_layers": 2,
"vis_encode_type": "simple",
"memory": null,
"goal_conditioning_type": "hyper",
"deterministic": false
},
"reward_signals": {
"extrinsic": {
"gamma": 0.99,
"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
}
},
"rnd": {
"gamma": 0.99,
"strength": 0.01,
"network_settings": {
"normalize": false,
"hidden_units": 64,
"num_layers": 3,
"vis_encode_type": "simple",
"memory": null,
"goal_conditioning_type": "hyper",
"deterministic": false
},
"learning_rate": 0.0001,
"encoding_size": null
}
},
"init_path": null,
"keep_checkpoints": 5,
"even_checkpoints": false,
"max_steps": 1000000,
"time_horizon": 128,
"summary_freq": 10000,
"threaded": false,
"self_play": null,
"behavioral_cloning": null
}
},
"env_settings": {
"env_path": "/content/ml-agents/training-envs-executables/linux/Pyramids/Pyramids",
"env_args": null,
"base_port": 5015,
"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": "Pyramids-course-20260925-v2",
"initialize_from": null,
"load_model": false,
"resume": false,
"force": false,
"train_model": false,
"inference": false,
"results_dir": "results"
},
"torch_settings": {
"device": "cpu"
},
"debug": false
} |