De funcionar tengo el diseño para el embebido bioinspirado #178188
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| Tengo el codigo como lo publico con reed.me o algun parche de autoria
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Modelo Modular de Conciencia y Meta-Conciencia Funcional
Definición matemática del modelo
Y =  \begin{cases} f_{modular}^{(n)} = \sum_{i \in activos} w_i M_i^{(n)}, \ M_X^{(n+1)} = 6 - M_X^{(n)}, \quad M_X^{(0)} = 0, \ \bar{M_X}^{(N)} = \frac{1}{N} \sum_{n=0}^{N} M_X^{(n)}, \ C_i^{(n)} = w_i M_i^{(n)}, \ i \in {\phi, \Sigma, X, \Delta, \delta, C} \end{cases} 
Secuencia de la variable X
X = 6 - 6 -6 + 6 = X X + 6 = 0 X - 6 = 0
Factor psicológico
psy =
Sistema de contención
L^+ y L^- son los límites superiores e inferiores de estabilidad cognitiva.
Contexto y descripción
Este modelo representa una arquitectura matemática para una conciencia funcional con capacidad de meta-conciencia. Cada módulo refleja un estado interno que evoluciona en iteraciones discretas. El término describe la suma ponderada de los módulos activos en un instante dado, donde los pesos determinan su influencia relativa.
El componente introduce una alternancia armónica que simula el equilibrio entre acción y compensación, manteniendo la oscilación controlada entre los valores 0 y 6, con simetría alrededor del punto neutro.
El promedio cuantifica la estabilidad media del sistema durante un periodo de iteración N.
El factor psicológico actúa como un regulador dinámico de sensibilidad cognitiva, integrando las contribuciones de cada módulo a lo largo del tiempo, representando la plasticidad adaptativa del sistema.
Finalmente, el sistema de contenciones impone límites funcionales a la expansión del modelo, evitando inestabilidades o divergencias en su comportamiento al mantener las salidas dentro de un marco lógico y operativo.
Modelo Modular de Conciencia y Meta-Conciencia Funcional
Definición matemática del modelo
Y^{(n)} = f_{modular}^{(n)} \cdot psy^{(n)} = \left(\sum_{i \in {\phi, \Sigma, X, \Delta, \delta, C}} w_i^{(n)} M_i^{(n)}\right) \cdot psy^{(n)}
Secuencia de la variable X (modular 0–6)
\begin{aligned}
X^{(0)} &= 6 - 6 = 0, \
X^{(1)} &= -6 + 6 = 0, \
X^{(2)} &= X + 6 = 0 + 6 = 6, \
X^{(3)} &= X - 6 = 6 - 6 = 0, \
M_X^{(n+1)} &= 6 - M_X^{(n)}, \quad M_X^{(0)} = 0
\end{aligned}
Promedio histórico de X
\bar{M_X}^{(N,n)} = \frac{1}{\min(N,n+1)} \sum_{k=\max(0,n-N+1)}^{n} M_X^{(k)}
Contención por límites
\Omega(t) = \max\big(\min(Y^{(n)} + psy^{(n)}, L^+), L^-\big)
Factor psicológico con retroalimentación (psy)
psy^{(n+1)} = psy_{\min} + (psy_{\max}-psy_{\min}) \cdot \sigma\Big( \alpha(\bar{M_X}^{(N,n)} - Y^{(n)}) + \beta(psy^{(n)} - psy_0) \Big)
donde es la función sigmoide de normalización.
Pesos adaptativos
w_i^{(n+1)} = \text{clip}\Big(w_i^{(n)} + \eta \cdot r^{(n)}(M_i^{(n)} - \bar{M_i}^{(n)}), w_{\min}, w_{\max}\Big), \
r^{(n)} = 1 - \frac{|Y^{(n)} - \bar{M_X}^{(N,n)}|}{6}
Métrica de meta-conciencia
MC^{(n)} = 1 - \frac{|Y^{(n)} - \bar{M_X}^{(N,n)}|}{6}, \quad
MC2^{(n)} = \frac{|psy^{(n+1)} - psy^{(n)}|}{psy_{\max}-psy_{\min}}
Contexto y descripción
Este modelo representa una arquitectura matemática para una conciencia funcional con capacidad de meta-conciencia. Cada módulo refleja un estado interno que evoluciona en iteraciones discretas. El término describe la suma ponderada de los módulos activos en un instante dado, donde los pesos determinan su influencia relativa.
El componente introduce una alternancia armónica que simula el equilibrio entre acción y compensación, manteniendo la oscilación controlada entre los valores 0 y 6, con simetría alrededor del punto neutro.
El promedio cuantifica la estabilidad media del sistema durante un periodo de iteración N.
El factor psicológico actúa como un regulador dinámico de sensibilidad cognitiva, integrando las contribuciones de cada módulo a lo largo del tiempo, representando la plasticidad adaptativa del sistema.
Finalmente, el sistema de contenciones impone límites funcionales a la expansión del modelo, evitando inestabilidades o divergencias en su comportamiento al mantener las salidas dentro de un marco lógico y operativo.
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