In this abstract, we discuss an alternative method to sampling for computing the answer to probabilistic expectation queries: enumerating values in the support of the model and adding their contribution to the expectation. We propose several criteria for a good … Continue reading →

Probabilistic program inference often involves choices between various strategies. Rather than try to make the choices in advance or delegate them to the user, we can use reinforcement learning to try different strategies and see which performs well. When a … Continue reading →