Bibliographic Details
| Title: |
The third stage in the Modelling System as first step in the third stage in Specific Artificial Intelligences for Artificial Research by Deduction within the first phase |
| Authors: |
García Pedraza, Rubén |
| Publisher Information: |
Ruben Garcia Pedraza, 2025. |
| Publication Year: |
2025 |
| Subject Terms: |
Artificial intelligence, Artificial Intelligence/history, Artificial Intelligence/legislation & jurisprudence, Artificial Intelligence/statistics & numerical data, Artificial Intelligence, Artificial Intelligence/economics, Artificial Intelligence/ethics, Artificial Intelligence/classification, Artificial Intelligence/standards, Artificial Intelligence/trends, Artificial Intelligence/supply & distribution |
| Description: |
The third stage in the Specific Modelling System represents the decision-making phase in Artificial Research by Deduction, where real objective auto-replications are generated to protect and improve mathematical models. These decisions—classified as protective or bettering—are made through two core methodologies under the theory of Impossible Probability: the Impact of the Defect (for identifying and preventing system vulnerabilities) and the Effective Distribution (for optimizing efficiency, efficacy, and productivity). Initially applied to specific-level models such as single virtual, comprehensive, predictive, and evolutionary models (virtual or actual), these decisions are stored in the Decisional System as a structured database. Additionally, knowledge objective auto-replications—both explicative and comprehensive—play a critical role in updating rational hypotheses and category structures. This stage forms a foundational step in the progressive construction of Specific Artificial Intelligences and their integration into the broader Global Artificial Intelligence architecture. |
| Document Type: |
Part of book or chapter of book |
| Language: |
English |
| DOI: |
10.5281/zenodo.16417280 |
| DOI: |
10.5281/zenodo.16417281 |
| Rights: |
CC BY |
| Accession Number: |
edsair.doi.dedup.....048913771512971fc99e1ddb74ce2057 |
| Database: |
OpenAIRE |