Graduate Program in Computer Engineering.Güngör, Tunga.Erkek, Cemal Acar.2023-03-162023-03-162010.CMPE 2010 E75https://digitalarchive.library.bogazici.edu.tr/handle/123456789/12174The main challenge of automated theorem proving is to find a way to shorten the search process. Therefore using a good heuristic method is essential. Although there are several heuristics that improve the search techniques, studies show that a single heuristic cannot cope with all type of problems. The nature of theorem proving problems makes it impossible to find the best universal heuristic, since each problem requires a different search approach. Choosing the right heuristic for a given problem is a difficult task even for an human expert. Machine learning techniques were applied successfully to construct a heuristic in several studies. Instead of constructing a heuristic from scratch, we propose to use the mixture of experts technique to combine the existing heuristics and construct a heuristic. Since each problem requires a different approach, our method uses the output data of a similar problem while learning the heuristic for each new problem. The results show that the combined heuristic is better than each individual heuristic used in combination.30cm.Neural networks (Computer science)Artificial intelligence.Automatic theorem proving.viii, 32 leaves;