String theory has far surpassed expectations in its ability to shed light on many areas of theoretical and mathematical physics. However, partly due to the immense size of the solution space, it is yet to be determined if our universe lives somewhere in the string landscape. In this talk, I will present how methods from computer science (genetic algorithms and reinforcement learning) can shed some light on these questions by exploring promising regions of the string landscape. Specifically, reinforcement learning and genetic algorithms are used to construct sums of line bundles and monad bundles on smooth Calabi-Yau threefolds, for compactifications of E8xE8 heterotic string theory.