Kernel Dynamics under Path Entropy Maximization

1. 1Define the kernel function as a dynamical variable
2. 2Apply path entropy maximization (Maximum Caliber, MaxCal) to the kernel function
3. 3Analyze the information geometry on probability space for each kernel
4. 4Study the trajectory through kernel space to understand representational structure dynamics

This research benefits AI engineers and ML researchers working on developing new frameworks for agent representation and information geometry, as it provides a novel approach to understanding kernel dynamics

💡 Treating the kernel function as a dynamical variable subject to path entropy maximization can reveal new insights into representational structure dynamics

💡 Kernel dynamics meets path entropy maximization!