Semantic based classification of search enhancements

AI research has developed numerous methods to solve state space problems. During the recent times, one Such strategy, Search Enhancements has performed a pivotal role in solving complex real world problems. Many different properties and taxonomies for these search enhancements appear in the literature. This work presents a new parameter for the classification of search enhancements with the intent to add a new dimension to the process of creating new enhancements as well as to develop a better understanding. This classification is based oil the semantics of the state space graph (or tree) generated and the problem domain. It is shown that semantics of a problem domain has been a vital aspect of the search enhancements. One semantic based search enhancement, the False-Move is described in this paper. This search enhancement in conjunction with the A* algorithm is used to solve the 8-puzzle problem and the results are presented.