Adaptive Particle Filters

Adaptive particle filters are advanced algorithms used to estimate the state of a system that changes over time, such as a vehicle's position or financial trends. They work by representing possible states with many "particles" and updating their likelihoods based on new data. Adaptively, these filters can change how many particles they use or how they weigh them, improving accuracy and efficiency as conditions evolve. This flexibility allows the system to better handle changing environments and uncertainties, making predictions more reliable without unnecessary computation.