Mandombe-Based Artificial Intelligence: Toward a Symbolic-Geometric Model of Computation

Abstract

This paper focuses on adapting Mandombe’s recursive symmetry to artificial intelligence design. It proposes a symbolic-geometric learning algorithm that uses inversion and rotation logic instead of linear weighting. Simulations demonstrate higher interpretability and resistance to data bias. This model aligns with decolonial computing principles and the epistemological independence envisioned by MEN-D research.

References:

Nsiangani K.M. (2016) From Mvemba Nzinga to Modern Puppets;

Nsiangani K. (2021) MEN-D Cryptography Symbolique.