exp03c_ppo_3x4_backplay_relaxed: checkpoint, config, evaluation files, model card

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Files changed (6) hide show

README.md +2 -2
config.json +43 -43
eval/eval_episodes.csv +601 -601
eval/summary.json +128 -128
train/progress.csv +0 -0
versions.json +9 -9

README.md CHANGED Viewed

@@ -38,7 +38,7 @@ model-index:
 # 4d-snake-exp03c-ppo-3x4-backplay-relaxed
-A `512x512` MLP policy for **4-dimensional snake on the 3^4 board** (81 cells, 8 moves): MaskablePPO trained from scratch, Backplay reverse curriculum (gate 0.8, window 8), 30,000,000 environment steps. From a length-1 start it completes the board in 0.0 % of deterministic episodes, evaluated with the protocol of [docs/evaluation.md](https://github.com/BurnyCoder/4d-snake-reinforcement-learning-agent/blob/main/docs/evaluation.md) (100 episodes x 3 seeds, masked `evaluate_policy`).
 **Negative result.** This network never fills the board from the true start (mean final fill 0.542). It is published so the failure is reproducible; the write-up linked below analyses why.
@@ -142,7 +142,7 @@ action, _ = model.predict(obs, action_masks=masks, deterministic=True)
 - `best_model.zip`: the evaluated checkpoint in Stable-Baselines3's save format (policy weights and optimizer state, https://stable-baselines3.readthedocs.io/en/master/guide/save_format.html).
 - `config.json`, `versions.json`: the run's resolved configuration and environment.
 - `eval/`: evaluation summary and one row per evaluation episode.
-- `train/progress.csv`: the SB3 training log; `figures/`: the learning curves.
 ## Licence

 # 4d-snake-exp03c-ppo-3x4-backplay-relaxed
+An MLP policy with two hidden layers of 512 units for **4-dimensional snake on the 3^4 board** (81 cells, 8 moves): MaskablePPO trained from scratch, Backplay reverse curriculum (gate 0.8, window 8), 30,000,000 environment steps. From a length-1 start it completes the board in 0.0 % of deterministic episodes, evaluated with the protocol of [docs/evaluation.md](https://github.com/BurnyCoder/4d-snake-reinforcement-learning-agent/blob/main/docs/evaluation.md) (100 episodes x 3 seeds, masked `evaluate_policy`).
 **Negative result.** This network never fills the board from the true start (mean final fill 0.542). It is published so the failure is reproducible; the write-up linked below analyses why.
 - `best_model.zip`: the evaluated checkpoint in Stable-Baselines3's save format (policy weights and optimizer state, https://stable-baselines3.readthedocs.io/en/master/guide/save_format.html).
 - `config.json`, `versions.json`: the run's resolved configuration and environment.
 - `eval/`: evaluation summary and one row per evaluation episode.
+- `train/progress.csv`: the SB3 training log; `figures/`: the learning curves and the fill histogram.
 ## Licence

config.json CHANGED Viewed

@@ -1,44 +1,44 @@
-{
-  "size": 3,
-  "ndim": 4,
-  "idle_mult": 4,
-  "r_food": 1.0,
-  "r_death": -1.0,
-  "r_win": 10.0,
-  "r_step": -0.001,
-  "shaping_coef": 0.0,
-  "n_envs": 2048,
-  "total_timesteps": 30000000,
-  "n_steps": 64,
-  "batch_size": 8192,
-  "n_epochs": 4,
-  "gamma": 0.99,
-  "gae_lambda": 0.95,
-  "lr_start": 0.0003,
-  "lr_end": 1e-05,
-  "clip_start": 0.2,
-  "clip_end": 0.05,
-  "ent_coef": 0.01,
-  "vf_coef": 0.5,
-  "max_grad_norm": 0.5,
-  "target_kl": 0.03,
-  "net_width": 512,
-  "device": "auto",
-  "torch_threads": 8,
-  "seed": 0,
-  "curriculum": 1,
-  "curriculum_window": 8,
-  "curriculum_delta": 4,
-  "curriculum_rho": 0.8,
-  "curriculum_min_eps": 500,
-  "p_true_start": 0.2,
-  "eval_episodes": 100,
-  "eval_every": 1310720,
-  "ckpt_every": 5242880,
-  "eval_seeds": "0,1,2",
-  "bench_steps": 200000,
-  "runs_dir": "runs",
-  "run_name": "exp03c_ppo_3x4_backplay_relaxed",
-  "model_path": "",
-  "policy": "route"
 }

+{
+  "size": 3,
+  "ndim": 4,
+  "idle_mult": 4,
+  "r_food": 1.0,
+  "r_death": -1.0,
+  "r_win": 10.0,
+  "r_step": -0.001,
+  "shaping_coef": 0.0,
+  "n_envs": 2048,
+  "total_timesteps": 30000000,
+  "n_steps": 64,
+  "batch_size": 8192,
+  "n_epochs": 4,
+  "gamma": 0.99,
+  "gae_lambda": 0.95,
+  "lr_start": 0.0003,
+  "lr_end": 1e-05,
+  "clip_start": 0.2,
+  "clip_end": 0.05,
+  "ent_coef": 0.01,
+  "vf_coef": 0.5,
+  "max_grad_norm": 0.5,
+  "target_kl": 0.03,
+  "net_width": 512,
+  "device": "auto",
+  "torch_threads": 8,
+  "seed": 0,
+  "curriculum": 1,
+  "curriculum_window": 8,
+  "curriculum_delta": 4,
+  "curriculum_rho": 0.8,
+  "curriculum_min_eps": 500,
+  "p_true_start": 0.2,
+  "eval_episodes": 100,
+  "eval_every": 1310720,
+  "ckpt_every": 5242880,
+  "eval_seeds": "0,1,2",
+  "bench_steps": 200000,
+  "runs_dir": "runs",
+  "run_name": "exp03c_ppo_3x4_backplay_relaxed",
+  "model_path": "",
+  "policy": "route"
 }

eval/eval_episodes.csv CHANGED Viewed

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