DavidVivancos/NeuraxonLife2.5ActiveBinary

NeuraxonLife2.5-100K-DeepTimeSeries: Artificial Life Neuraxon Neural Network Simulation Deep Time Series Dataset (Active Binary Exploration)

The Dataset is a companion suporting material for the upcoming paper: "The Neutral Buffer State: Trinary Logic Advantage in Branching Ratio Stability for Continuous-Time Networks" by David Vivancos & Dr José Sanchez

Dataset Description

The NeuraxonLife 2.5 Deep Time Series Dataset is a massive, comprehensive collection of simulation data from the Neuraxon Game of Life environment. It tracks the evolution of over 100,000 autonomous agents ("NxErs") evolving biologically-plausible neural networks under survival pressures.

This dataset represents a significant expansion over previous versions, featuring "Deep Time Series" exploration with over 279 million plasticity events and high-resolution per-agent time series data.

Also validatie the original Neuraxon 1.0 paper: 'A New Neural Growth & Computation Blueprint' by David Vivancos https://www.vivancos.com/ & Dr. Jose Sanchez https://josesanchezgarcia.com/ for Qubic Science. https://qubic.org/

Paper Reference: Neuraxon: A New Neural Growth & Computation Blueprint

Dataset Summary

This dataset provides granular insights into emergent neural computation in an artificial life setting. It covers 2,791 distinct simulation games involving complex neural phenomena.

Citation

@dataset{NeuraxonLife2.5-TimeSeriesActiveBinary,
  title={Neuraxon Game of Life 2.5 Research Dataset: Deep Time Series Exploration Active Binnary Exploration},
  author={Vivancos, David and Sanchez, Jose},
  year={2026},
  publisher={Hugging Face},
  version={2.5.0},
  url={https://huggingface.co/datasets/DavidVivancos/NeuraxonLife2.5ActiveBinary}
}

Authors & Curators

• David Vivancos / Artificiology Research - Qubic Science
• Dr. Jose Sanchez / UNIR - Qubic Science Contact: For questions or issues, please open a GitHub issue at https://github.com/DavidVivancos/Neuraxon.