# 🛡️ Systems Modeling and Cognitive Audits for Hypercert Ecosystems

**Active Inference Institute** (2022) · *Zenodo*

[![DOI](https://img.shields.io/badge/DOI-10.5281%2Fzenodo.7626769-blue)](https://doi.org/10.5281/zenodo.7626769)

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## Abstract

> This paper discusses the development of frameworks and tools for applied Active Inference in the context of Decentralized Science (DeSci) and Hypercert ecosystems. It aims to enhance the flexibility and utility of Hypercerts through the creation of an Active Entity Ontology for Science (AEOS) and the implementation of Active Blockference.

## Keywords

`Hypercerts` · `DeSci` · `decentralized science` · `Active Blockference` · `AEOS` · `cognitive audits` · `public goods funding` · `systems modeling`

## Key Contributions

- Introduction of an Active Entity Ontology for Science (AEOS) to describe interactions within Hypercert ecosystems.
- Development of Active Blockference for simulating cognitive processes in Hypercert ecosystems.
- Creation of educational resources and tools for cognitive audits of Hypercert protocols.
- Rigorous analysis of Hypercert funding mechanisms to enhance their efficacy in DeSci.

## Methods

- Utilization of Active Inference frameworks for modeling interactions in Hypercert ecosystems.
- Implementation of multi-agent simulations to explore cognitive and behavioral dynamics.
- Engagement in informative interviews with stakeholders to understand the Hypercert landscape.
- Development of entity diagrams and simulations tailored to researcher needs.

## 🎯 Consulting & Tutoring

**Available for AI Research Consulting and Tutoring.** [Contact Daniel Ari Friedman, PhD](https://danielarifriedman.com/) for collaboration on Active Inference, Bayesian modeling, and computational biology.

## Citation

```bibtex
@article{2022_HypercertEcosystems,
  author = {Active Inference Institute},
  title = {{Systems Modeling and Cognitive Audits for Hypercert Ecosystems}},
  journal = {Zenodo},
  year = {2022},
  doi = {10.5281/zenodo.7626769},
}
```

## File Inventory

- `AGENTS.md` (1,872 bytes)
- `2022_HypercertEcosystems.pdf` (76,972 bytes)
- `README.md` (1,577 bytes)
- `SKILL.md` (1,780 bytes)