Update README.md

dataset description

README.md

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 ---
+pretty_name: MultiNxon2 NAS Runs (Neuraxon Game of Life)
+tags:
+  - neural-architecture-search
+  - artificial-life
+  - neuroscience
+  - simulation
+  - neuraxon
 license: cc-by-sa-4.0
 ---
+
+# MultiNxon2 — NAS Runs for the Neuraxon Game of Life
+
+This dataset contains the raw outputs of many **Neural Architecture Search (NAS)**
+runs for the **Neuraxon Game of Life** — an artificial-life simulation where
+small spiking "brains" (NxErs) live, eat, mate and explore a world. Each NAS run
+searches over brain hyper-parameters to find the architecture that best survives
+and behaves, scored by a single `fitness` value plus a set of biology-inspired
+metrics (M1–M10).
+
+The runs were collected over several days and span Neuraxon internal versions
+**v166 → v195**. Each version tweaks the search space or the fitness/selection
+logic, so the collection is also a longitudinal record of how the search itself
+evolved.
+
+## Folder layout
+
+One NAS run = one folder named by its start timestamp:
+
+```
+20260512_212222/
+20260514_075838/
+...
+20260531_163524/
+```
+
+Each run folder contains:
+
+| File / folder | What it is |
+|---|---|
+| `nas_log.csv` | **Main results table** — one row per trial (architecture). Start here. |
+| `nas_best.json` | The single best architecture of the run. |
+| `nas_top1.json`, `nas_top2.json`, `nas_top3.json` | The top-3 architectures. |
+| `trial_NNN__arch.json` | The full hyper-parameters for trial `NNN`. |
+| `trial_NNN/` | Per-trial game outputs (the actual simulation logs for that architecture). |
+
+Inside a `trial_NNN/` folder (newer runs nest seed repeats as `rep0/`, `rep1/`,
+`rep2/`; older runs use sibling `trial_NNN_s<seed>/` folders):
+
+| File | What it is |
+|---|---|
+| `nxon2_<id>__BestFitness.json` | Best-of-run game state for each scoring dimension: |
+| `..._BestFoodFound.json`, `..._BestFoodTaken.json` | …food found / taken, |
+| `..._BestMates.json`, `..._BestTimeLived.json`, `..._BestWorldExplorer.json` | …mates, lifespan, exploration. |
+| `..._KeyMetrics.txt` | Human-readable summary of the run's key metrics. |
+| `..._LifespanLog.txt` | Per-agent lifespan / population log. |
+| `..._MembraneDiag.txt` | Membrane / firing diagnostics. |
+| `..._Completed_<timestamp>.json` | Final completed game record. |
+
+## `nas_log.csv` columns (the important ones)
+
+`nas_log.csv` has ~52 columns. The key ones:
+
+- `trial_id` — index of the trial within the run.
+- `fitness` — the value being optimised (higher is better).
+- `arch_summary` — the **full hyper-parameter string** for that architecture
+  (firing thresholds, connection probability, learning rate, topology, etc.).
+- `is_global_best` — `1` for the run's winning architecture.
+- `M1`–`M10` — paper-fidelity metrics (e.g. `M1` = excitatory firing band,
+  `M1_neutral` / `M1_inh` = rest / inhibition fractions, plus synchrony,
+  plasticity and other dynamics measures).
+- Survival / behaviour: `final_alive`, `peak_alive`, `alive_mean`,
+  `went_extinct`, `surv_score`, `expl_rate`.
+- Reliability: `n_repeats`, `n_repeats_ok`, `fitness_std_reps`, `M1_std`
+  (later versions re-run the same architecture across seeds to average out noise).
+- Bookkeeping: `completed_at_iso`, `wall_actual_s`, `total_rounds`, `error`.
+
+## Quick start
+
+```python
+import pandas as pd
+
+# point at any run folder
+df = pd.read_csv("20260531_163524/nas_log.csv")
+
+# best architecture in that run
+best = df.sort_values("fitness", ascending=False).iloc[0]
+print(best["fitness"], best["arch_summary"])
+```
+
+## Notes
+
+- All paths in the original logs use `\...`; that prefix is just the
+  source drive and can be ignored.
+- This is **raw research output**: column sets and folder conventions shift
+  slightly between versions as the search evolved.
+
+## License
+
+Released under CC-BY-4.0-SA
+
+## Citation
+```bibtex
+@dataset{NeuraxonGameOFLifeResearhNAS-5-MultiNxon2NAS
+  title={Neuraxon Game of Life 5 Research Dataset: NAS Multi Nxon Exploration},
+  author={Vivancos, David and Sanchez, Jose},
+  year={2026},
+  publisher={Hugging Face},
+  version={1.0.0},
+  url={https://huggingface.co/datasets/DavidVivancos/MultiNxon2NAS}
+}
+```
+## Authors & Curators
+*   **David Vivancos** / Artificiology Research (https://artificiology.com) - [Qubic Science](https://qubic.org/)
+*   **Dr. Jose Sanchez** / UNIR - [Qubic Science](https://qubic.org/)
+**Contact:** For questions or issues, please open a GitHub issue at [https://github.com/DavidVivancos/Neuraxon](https://github.com/DavidVivancos/Neuraxon).