The key component of such a process is the mathematical algorithm that must determine what to do in response to the input. The solution to problem b is often the most difficult to determine. To address this point, detailed simulations of the system of interest must be combined, if possible, with extensive human input. The combined effect of all things that are either of unknown form or origin or arise from known effects can be regarded as noise. It is generally treated by tools of probability.
Uncertainty refers to varying degrees of belief about various features of a process.
For example, given a variety of sensors for measuring temperature at a point, measurement by one sensor may be believed more accurate than that by another. The actual belief can be assigned using the tools of fuzzy analysis in which numerical estimates of belief are blended with our expertise. Problems d and e are probably the key difficulties of artificial intelligence today. Problem e arises when two experts give opposing opinions about what is going on or what policy is to be followed. Although criteria abound for reaching decisions based on multiple sources of information, the area is still at the stage of basic research and trial.