The goal of this research project is to explore the combination of statistical modeling with heuristic search techniques to solve hard computational problems in two areas : construction of a physical map of the human DNA and automatic learning in computer chess. The approach consists of formulating statistical models that are trained on data to automatically adjust broad parameters that define the knowledge encoded in the program. This is combined with traditional AI heuristic search techniques when exhaustive search of the parameter or problem space is not possible. The results of this research will allow programs to exhibit a rudimentary form of learning in areas like chess games, as well as allow a physical map of the entire human DNA to be constructed in record time of about six months which will allow geneticists to find the cause of any genetic disorder and in turn increases the chance of finding cures for these genetic disorders.
