Path Patching

Path patching encompasses a range of techniques focused on analyzing and manipulating paths within complex systems, aiming to understand behavior, predict outcomes, or optimize performance. Current research explores diverse applications, from predicting fatigue crack growth in materials science using neural networks and path-slicing methods to optimizing robot motion planning through path defragmentation in factored state spaces and improving the efficiency of shortest path algorithms in dynamic networks via deep learning. These advancements have implications for diverse fields, including structural health monitoring, robotics, and network optimization, by providing more efficient and accurate methods for analyzing and controlling complex systems.