Abstract
Universal search is the asymptotically fastest method to solve a wide class of inversion problems. Recently this method has been used to develop several efficient optimal general problem solvers. However the huge constant slowdown factor associated with this algorithm prevents it from widespread practical application. Our endeavor is to reduce this constant slowdown factor in the non incremental version of the algorithm which can be easily extended in the incremental version. While searching the exponential program space, universal search method generates and tests several equivalent programs. Pruning equivalent programs will evidently reduce the search space and consequently the search time. Experimental analysis reveals a huge speed up of the search method. Even though pruning is applied it has also been shown theoretically that if universal search can find a solution then the proposed search method can always find a solution for a given problem.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
