| --- |
| 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). |
