In this seminar, we will study uncertainty in the context of reasoning, planning, and scheduling. For reasoning about actions, we will look into stochastic extensions of the Situation Calculus, a well-known formalism for reasoning about dynamic domains. In the classical Situation Calculus, all actions are deterministic. In this seminar, we will learn about extensions that allow non-deterministic and probabilistic actions. For planning, we will investigate probabilistic extensions to classical planning frameworks such as the Planning Domain Definition Language (PDDL) and compare them to Markov Decision Processes (MDPs). For scheduling, we will learn about mechanisms for solving scheduling problems with probabilistic task durations.