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Beyond Shannon: The Dynamic Entropy Model (DEM) Mathematics
- Entropy is traditionally viewed as a measure of uncertainty and disorder, but the Dynamic Entropy Model (DEM) proposes a new perspective.
- Shannon's entropy model is limited by static probability distributions, while DEM allows for dynamic evolution of entropy.
- DEM redefines entropy as a manipulable variable in AI, quantum systems, biology, and complex adaptive systems.
- In DEM, entropy is defined as a function of time, allowing for external control and manipulation.
- Dynamic probability evolution in open systems challenges the static nature of Shannon's entropy model.
- Entropy feedback control enables the regulation of entropy through external interventions in AI, robotics, and biological systems.
- Maxwell's Demon concept is realized as an entropy-aware feedback controller in DEM.
- Entropy engineering involves optimizing entropy for order and diversity in complex systems using control theory principles.
- DEM implications span AI, quantum computing, and complex systems, offering new possibilities for understanding and control.
- Moving beyond Shannon's static entropy model, DEM presents entropy as a dynamic and controllable force for mastering complex systems.
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