Penalty-function method based on a new voting principles and its applications in multi-propositional reasoning systems

The non-monotonic reasoning system based on penalty function was originally introduced by Pinkas in 1995. The main idea of this method is to get unknown knowledge via the voting method according to some known knowledge. However, the penalty function method, when applied to the problem of intelligent route planning, cannot effectively reflect human intelligence. A new voting principle and a new method to construct its penalty function are presented. Experimental results show that, in some real applications, our new penalty function is more reasonable and effective than that of Pinkas.