First Commit
Browse files- README.md +35 -0
- SoccerTwos.onnx +3 -0
- SoccerTwos/SoccerTwos-5499978.onnx +3 -0
- SoccerTwos/SoccerTwos-5499978.pt +3 -0
- SoccerTwos/SoccerTwos-5999934.onnx +3 -0
- SoccerTwos/SoccerTwos-5999934.pt +3 -0
- SoccerTwos/SoccerTwos-6000216.onnx +3 -0
- SoccerTwos/SoccerTwos-6000216.pt +3 -0
- SoccerTwos/SoccerTwos-6499992.onnx +3 -0
- SoccerTwos/SoccerTwos-6499992.pt +3 -0
- SoccerTwos/SoccerTwos-6999876.onnx +3 -0
- SoccerTwos/SoccerTwos-6999876.pt +3 -0
- SoccerTwos/SoccerTwos-7499988.onnx +3 -0
- SoccerTwos/SoccerTwos-7499988.pt +3 -0
- SoccerTwos/SoccerTwos-7600048.onnx +3 -0
- SoccerTwos/SoccerTwos-7600048.pt +3 -0
- SoccerTwos/SoccerTwos-7692216.onnx +3 -0
- SoccerTwos/SoccerTwos-7692216.pt +3 -0
- SoccerTwos/checkpoint.pt +3 -0
- SoccerTwos/events.out.tfevents.1706583384.300331b929f9.4572.0 +3 -0
- SoccerTwos/events.out.tfevents.1706596433.300331b929f9.59444.0 +3 -0
- SoccerTwos/events.out.tfevents.1706596459.300331b929f9.59607.0 +3 -0
- SoccerTwos/events.out.tfevents.1706596493.300331b929f9.59805.0 +3 -0
- SoccerTwos/events.out.tfevents.1706597868.300331b929f9.65706.0 +3 -0
- SoccerTwos/events.out.tfevents.1706599197.300331b929f9.71410.0 +3 -0
- SoccerTwos/events.out.tfevents.1706601694.300331b929f9.82177.0 +3 -0
- SoccerTwos/events.out.tfevents.1706602116.300331b929f9.84046.0 +3 -0
- SoccerTwos/events.out.tfevents.1706602400.300331b929f9.85316.0 +3 -0
- SoccerTwos/events.out.tfevents.1706602617.300331b929f9.86301.0 +3 -0
- config.json +1 -0
- configuration.yaml +84 -0
- run_logs/Player-0.log +62 -0
- run_logs/timers.json +417 -0
- run_logs/training_status.json +111 -0
README.md
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---
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library_name: ml-agents
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tags:
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- SoccerTwos
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- deep-reinforcement-learning
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- reinforcement-learning
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- ML-Agents-SoccerTwos
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---
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# **poca** Agent playing **SoccerTwos**
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This is a trained model of a **poca** agent playing **SoccerTwos**
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using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
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## Usage (with ML-Agents)
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The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
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We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
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- A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
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browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
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- A *longer tutorial* to understand how works ML-Agents:
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https://huggingface.co/learn/deep-rl-course/unit5/introduction
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### Resume the training
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```bash
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mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
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```
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### Watch your Agent play
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You can watch your agent **playing directly in your browser**
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1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
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2. Step 1: Find your model_id: ucheokechukwu/poca-SoccerTwos
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3. Step 2: Select your *.nn /*.onnx file
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4. Click on Watch the agent play 👀
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SoccerTwos.onnx
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config.json
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{"default_settings": null, "behaviors": {"SoccerTwos": {"trainer_type": "poca", "hyperparameters": {"batch_size": 2048, "buffer_size": 20480, "learning_rate": 0.0005, "beta": 0.005, "epsilon": 0.2, "lambd": 0.95, "num_epoch": 3, "learning_rate_schedule": "constant", "beta_schedule": "constant", "epsilon_schedule": "constant"}, "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}}}, "init_path": null, "keep_checkpoints": 5, "even_checkpoints": false, "max_steps": 15000000, "time_horizon": 1000, "summary_freq": 10000, "threaded": false, "self_play": {"save_steps": 50000, "team_change": 200000, "swap_steps": 2000, "window": 20, "play_against_latest_model_ratio": 0.4, "initial_elo": 1540.0}, "behavioral_cloning": null}}, "env_settings": {"env_path": "./training-envs-executables/SoccerTwos.x86_64", "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": "SoccerTwos", "initialize_from": null, "load_model": false, "resume": true, "force": false, "train_model": false, "inference": false, "results_dir": "results"}, "torch_settings": {"device": null}, "debug": false}
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configuration.yaml
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default_settings: null
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behaviors:
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SoccerTwos:
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trainer_type: poca
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hyperparameters:
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batch_size: 2048
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buffer_size: 20480
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learning_rate: 0.0005
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beta: 0.005
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epsilon: 0.2
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lambd: 0.95
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num_epoch: 3
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learning_rate_schedule: constant
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beta_schedule: constant
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epsilon_schedule: constant
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checkpoint_interval: 500000
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network_settings:
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normalize: false
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hidden_units: 512
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num_layers: 2
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vis_encode_type: simple
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memory: null
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goal_conditioning_type: hyper
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deterministic: false
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reward_signals:
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extrinsic:
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gamma: 0.99
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strength: 1.0
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network_settings:
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normalize: false
|
31 |
+
hidden_units: 128
|
32 |
+
num_layers: 2
|
33 |
+
vis_encode_type: simple
|
34 |
+
memory: null
|
35 |
+
goal_conditioning_type: hyper
|
36 |
+
deterministic: false
|
37 |
+
init_path: null
|
38 |
+
keep_checkpoints: 5
|
39 |
+
even_checkpoints: false
|
40 |
+
max_steps: 15000000
|
41 |
+
time_horizon: 1000
|
42 |
+
summary_freq: 10000
|
43 |
+
threaded: false
|
44 |
+
self_play:
|
45 |
+
save_steps: 50000
|
46 |
+
team_change: 200000
|
47 |
+
swap_steps: 2000
|
48 |
+
window: 20
|
49 |
+
play_against_latest_model_ratio: 0.4
|
50 |
+
initial_elo: 1540.0
|
51 |
+
behavioral_cloning: null
|
52 |
+
env_settings:
|
53 |
+
env_path: ./training-envs-executables/SoccerTwos.x86_64
|
54 |
+
env_args: null
|
55 |
+
base_port: 5005
|
56 |
+
num_envs: 1
|
57 |
+
num_areas: 1
|
58 |
+
timeout_wait: 60
|
59 |
+
seed: -1
|
60 |
+
max_lifetime_restarts: 10
|
61 |
+
restarts_rate_limit_n: 1
|
62 |
+
restarts_rate_limit_period_s: 60
|
63 |
+
engine_settings:
|
64 |
+
width: 84
|
65 |
+
height: 84
|
66 |
+
quality_level: 5
|
67 |
+
time_scale: 20
|
68 |
+
target_frame_rate: -1
|
69 |
+
capture_frame_rate: 60
|
70 |
+
no_graphics: true
|
71 |
+
no_graphics_monitor: false
|
72 |
+
environment_parameters: null
|
73 |
+
checkpoint_settings:
|
74 |
+
run_id: SoccerTwos
|
75 |
+
initialize_from: null
|
76 |
+
load_model: false
|
77 |
+
resume: true
|
78 |
+
force: false
|
79 |
+
train_model: false
|
80 |
+
inference: false
|
81 |
+
results_dir: results
|
82 |
+
torch_settings:
|
83 |
+
device: null
|
84 |
+
debug: false
|
run_logs/Player-0.log
ADDED
@@ -0,0 +1,62 @@
|
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|
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|
1 |
+
Mono path[0] = '/content/content/MyDrive/MLOPs_Projects/HuggingFace/ReinforcementLearning_Course/Unit_7/ml-agents/training-envs-executables/SoccerTwos_Data/Managed'
|
2 |
+
Mono config path = '/content/content/MyDrive/MLOPs_Projects/HuggingFace/ReinforcementLearning_Course/Unit_7/ml-agents/training-envs-executables/SoccerTwos_Data/MonoBleedingEdge/etc'
|
3 |
+
Preloaded 'lib_burst_generated.so'
|
4 |
+
Preloaded 'libgrpc_csharp_ext.x64.so'
|
5 |
+
Initialize engine version: 2021.3.14f1 (eee1884e7226)
|
6 |
+
[Subsystems] Discovering subsystems at path /content/content/MyDrive/MLOPs_Projects/HuggingFace/ReinforcementLearning_Course/Unit_7/ml-agents/training-envs-executables/SoccerTwos_Data/UnitySubsystems
|
7 |
+
Forcing GfxDevice: Null
|
8 |
+
GfxDevice: creating device client; threaded=0; jobified=0
|
9 |
+
NullGfxDevice:
|
10 |
+
Version: NULL 1.0 [1.0]
|
11 |
+
Renderer: Null Device
|
12 |
+
Vendor: Unity Technologies
|
13 |
+
ALSA lib confmisc.c:855:(parse_card) cannot find card '0'
|
14 |
+
ALSA lib conf.c:5178:(_snd_config_evaluate) function snd_func_card_inum returned error: No such file or directory
|
15 |
+
ALSA lib confmisc.c:422:(snd_func_concat) error evaluating strings
|
16 |
+
ALSA lib conf.c:5178:(_snd_config_evaluate) function snd_func_concat returned error: No such file or directory
|
17 |
+
ALSA lib confmisc.c:1334:(snd_func_refer) error evaluating name
|
18 |
+
ALSA lib conf.c:5178:(_snd_config_evaluate) function snd_func_refer returned error: No such file or directory
|
19 |
+
ALSA lib conf.c:5701:(snd_config_expand) Evaluate error: No such file or directory
|
20 |
+
ALSA lib pcm.c:2664:(snd_pcm_open_noupdate) Unknown PCM default
|
21 |
+
FMOD failed to initialize the output device.: "Error initializing output device. " (60)
|
22 |
+
Forced to initialize FMOD to to the device driver's system output rate 48000, this may impact performance and/or give inconsistent experiences compared to selected sample rate 48000
|
23 |
+
ALSA lib confmisc.c:855:(parse_card) cannot find card '0'
|
24 |
+
ALSA lib conf.c:5178:(_snd_config_evaluate) function snd_func_card_inum returned error: No such file or directory
|
25 |
+
ALSA lib confmisc.c:422:(snd_func_concat) error evaluating strings
|
26 |
+
ALSA lib conf.c:5178:(_snd_config_evaluate) function snd_func_concat returned error: No such file or directory
|
27 |
+
ALSA lib confmisc.c:1334:(snd_func_refer) error evaluating name
|
28 |
+
ALSA lib conf.c:5178:(_snd_config_evaluate) function snd_func_refer returned error: No such file or directory
|
29 |
+
ALSA lib conf.c:5701:(snd_config_expand) Evaluate error: No such file or directory
|
30 |
+
ALSA lib pcm.c:2664:(snd_pcm_open_noupdate) Unknown PCM default
|
31 |
+
FMOD failed to initialize the output device.: "Error initializing output device. " (60)
|
32 |
+
FMOD initialized on nosound output
|
33 |
+
Begin MonoManager ReloadAssembly
|
34 |
+
- Completed reload, in 1.283 seconds
|
35 |
+
ERROR: Shader Sprites/Default shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
36 |
+
ERROR: Shader Sprites/Mask shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
37 |
+
ERROR: Shader Legacy Shaders/VertexLit shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
38 |
+
WARNING: Shader Unsupported: 'Standard (Specular setup)' - All subshaders removed
|
39 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
40 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
41 |
+
ERROR: Shader Standard (Specular setup) shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
42 |
+
WARNING: Shader Unsupported: 'Standard (Specular setup)' - All subshaders removed
|
43 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
44 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
45 |
+
WARNING: Shader Unsupported: 'Autodesk Interactive' - All subshaders removed
|
46 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
47 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
48 |
+
ERROR: Shader Autodesk Interactive shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
49 |
+
WARNING: Shader Unsupported: 'Autodesk Interactive' - All subshaders removed
|
50 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
51 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
52 |
+
WARNING: Shader Unsupported: 'Standard' - All subshaders removed
|
53 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
54 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
55 |
+
ERROR: Shader Standard shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
56 |
+
WARNING: Shader Unsupported: 'Standard' - All subshaders removed
|
57 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
58 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
59 |
+
UnloadTime: 1.095756 ms
|
60 |
+
Registered Communicator in Agent.
|
61 |
+
ERROR: Shader UI/Default shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
62 |
+
requesting resize 84 x 84
|
run_logs/timers.json
ADDED
@@ -0,0 +1,417 @@
|
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|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"name": "root",
|
3 |
+
"gauges": {
|
4 |
+
"SoccerTwos.Policy.Entropy.mean": {
|
5 |
+
"value": 1.6669374704360962,
|
6 |
+
"min": 1.6359543800354004,
|
7 |
+
"max": 1.6686762571334839,
|
8 |
+
"count": 7
|
9 |
+
},
|
10 |
+
"SoccerTwos.Policy.Entropy.sum": {
|
11 |
+
"value": 33285.40625,
|
12 |
+
"min": 28373.9921875,
|
13 |
+
"max": 35656.47265625,
|
14 |
+
"count": 7
|
15 |
+
},
|
16 |
+
"SoccerTwos.Environment.EpisodeLength.mean": {
|
17 |
+
"value": 69.27777777777777,
|
18 |
+
"min": 56.20238095238095,
|
19 |
+
"max": 69.27777777777777,
|
20 |
+
"count": 7
|
21 |
+
},
|
22 |
+
"SoccerTwos.Environment.EpisodeLength.sum": {
|
23 |
+
"value": 19952.0,
|
24 |
+
"min": 16200.0,
|
25 |
+
"max": 20212.0,
|
26 |
+
"count": 7
|
27 |
+
},
|
28 |
+
"SoccerTwos.Self-play.ELO.mean": {
|
29 |
+
"value": 1539.4471772250445,
|
30 |
+
"min": 1527.7409143925404,
|
31 |
+
"max": 1545.935715339572,
|
32 |
+
"count": 7
|
33 |
+
},
|
34 |
+
"SoccerTwos.Self-play.ELO.sum": {
|
35 |
+
"value": 221680.3935204064,
|
36 |
+
"min": 210247.2572861818,
|
37 |
+
"max": 258303.83899147165,
|
38 |
+
"count": 7
|
39 |
+
},
|
40 |
+
"SoccerTwos.Step.mean": {
|
41 |
+
"value": 7759836.0,
|
42 |
+
"min": 7699856.0,
|
43 |
+
"max": 7759836.0,
|
44 |
+
"count": 7
|
45 |
+
},
|
46 |
+
"SoccerTwos.Step.sum": {
|
47 |
+
"value": 7759836.0,
|
48 |
+
"min": 7699856.0,
|
49 |
+
"max": 7759836.0,
|
50 |
+
"count": 7
|
51 |
+
},
|
52 |
+
"SoccerTwos.Policy.ExtrinsicBaselineEstimate.mean": {
|
53 |
+
"value": -0.02039300464093685,
|
54 |
+
"min": -0.06732017546892166,
|
55 |
+
"max": 0.006477044429630041,
|
56 |
+
"count": 7
|
57 |
+
},
|
58 |
+
"SoccerTwos.Policy.ExtrinsicBaselineEstimate.sum": {
|
59 |
+
"value": -2.9161996841430664,
|
60 |
+
"min": -10.462895393371582,
|
61 |
+
"max": 0.8679239749908447,
|
62 |
+
"count": 7
|
63 |
+
},
|
64 |
+
"SoccerTwos.Policy.ExtrinsicValueEstimate.mean": {
|
65 |
+
"value": -0.018799273297190666,
|
66 |
+
"min": -0.06896685063838959,
|
67 |
+
"max": 0.014638231135904789,
|
68 |
+
"count": 7
|
69 |
+
},
|
70 |
+
"SoccerTwos.Policy.ExtrinsicValueEstimate.sum": {
|
71 |
+
"value": -2.68829607963562,
|
72 |
+
"min": -10.482961654663086,
|
73 |
+
"max": 1.9615229368209839,
|
74 |
+
"count": 7
|
75 |
+
},
|
76 |
+
"SoccerTwos.Environment.CumulativeReward.mean": {
|
77 |
+
"value": 0.0,
|
78 |
+
"min": 0.0,
|
79 |
+
"max": 0.0,
|
80 |
+
"count": 7
|
81 |
+
},
|
82 |
+
"SoccerTwos.Environment.CumulativeReward.sum": {
|
83 |
+
"value": 0.0,
|
84 |
+
"min": 0.0,
|
85 |
+
"max": 0.0,
|
86 |
+
"count": 7
|
87 |
+
},
|
88 |
+
"SoccerTwos.Policy.ExtrinsicReward.mean": {
|
89 |
+
"value": 0.017475523315109574,
|
90 |
+
"min": -0.14296273452154598,
|
91 |
+
"max": 0.18005912183965528,
|
92 |
+
"count": 7
|
93 |
+
},
|
94 |
+
"SoccerTwos.Policy.ExtrinsicReward.sum": {
|
95 |
+
"value": 2.498999834060669,
|
96 |
+
"min": -23.017000257968903,
|
97 |
+
"max": 28.629400372505188,
|
98 |
+
"count": 7
|
99 |
+
},
|
100 |
+
"SoccerTwos.Environment.GroupCumulativeReward.mean": {
|
101 |
+
"value": 0.017475523315109574,
|
102 |
+
"min": -0.14296273452154598,
|
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