PF stands for "potential fields," which are mathematical models used in fields such as geology, physics, and robotics. They are considered wishy-washy because they are based on assumptions and simplifications that may not accurately represent real-world situations.
PFs work by assigning a numerical value, known as a potential, to every point in a space. The potential at a given point is influenced by nearby objects or forces, and the overall shape of the potential field can give information about the location and strength of these objects or forces.
One major limitation of using PFs is that they are highly dependent on the specific assumptions and parameters chosen for the model. This can lead to inaccurate or inconsistent results. Additionally, PFs may not be suitable for complex or dynamic systems, as they are often based on static or simplified environments.
No, PFs are not suitable for all types of problems. They are best used for simple, static systems where the assumptions and parameters chosen for the model accurately represent the real-world situation. PFs may also not be suitable for problems that require high levels of precision or accuracy.
Researchers are constantly working on improving PF models by incorporating more complex and realistic assumptions, as well as developing techniques to validate and verify the results. Additionally, using PFs in conjunction with other modeling methods can help to overcome some of their limitations.