Dynamic fuzzy logic leads to more adequate “and” and “or” operations

In the traditional (static) fuzzy logic approach, we select an “and”-operation (t-norm) and an “or”-operation (t-conorm). The result of applying these selected op-erations may be somewhat different from the actual expert’s degrees of belief in the corresponding logical combinations A&B and A∨B of the original statements – since these degrees depend not only on the expert’s degrees of belief in statements A and B, but also in the extent to which the statements A and B are dependent. We show that dynamic fuzzy logic enables us to automatically take this dependence into account – and thus, leads to more adequate “and”- and “or”-operations. 1 Formulation of the Problem “And ” and “or ” operations in fuzzy logic. In many practical applications, expert rules are formulated by using imprecise (“fuzzy”) words from natural language, like “small”, “medium size”, or “large”. For example, medical recommendations about a tumor depend on whether the tumor is small, medium size, or large. Similarly, expert advise on how to avoid collision with a car in front depend on whether the distance to this car is small, medium, o