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social and non_social × seeds 0–9), each trained with PPO for 20,000
updates × 40 episodes × 100 steps. 20/20 units completed on the first attempt.{social,non_social}/seed_XXXX/attempt_01/checkpoints/latest.safetensors —
trained chaser+explorer weights (safetensors; config/metrics in metadata).paper_rollouts/*.safetensors — 25×500-step analysis rollouts per pair:
per-timestep hidden states, positions, actions, and social-event flags
(schema v3, time-aligned; degenerate episodes flagged).paper_random_eval.jsonl — standardized random-opponent evaluation.derived/{tables,reports}/ — canonical tables and the per-experiment report.cross_architecture_study/ — the four-architecture comparison report,
figures, and cross-architecture PLSC/CKA data.manifest.json, raw_records.jsonl, launch_gate.json,
triton_equivalence.json — provenance.cross_architecture_study/report.md for the four-architecture comparison.
Headline: the architectures do not learn the same internal representations —
only the RNN develops genuine internal shared dynamics at low mutual vision.1from huggingface_hub import hf_hub_download
2from mouse_run_run.serialization import load_checkpoint
3from mouse_run_run.policy import build_policy
4
5path = hf_hub_download("JacobLinCool/mouse-run-run-2-ssm",
6 "social/seed_0000/attempt_01/checkpoints/latest.safetensors")
7config, metrics, chaser_state, explorer_state = load_checkpoint(path)
8chaser = build_policy(config["architecture"], config["env"]["observation_size"],
9 hidden_size=config["hidden_size"])
10chaser.load_state_dict(chaser_state)