The SPUDD planner was applied to the IPPC instances, solving each optimally. SPUDD uses a dynamic abstraction method for solving MDPs using algebraic decision diagrams (ADDs) to represent value functions and policies. ADDs are generalizations of ordered binary decision diagrams (BDDs) that allow non-boolean labels at terminal nodes. This representational technique allows one to describe a value function (or policy) as a function of the variables describing the domain rather than in the classical "tabular" way. The decision graph used to represent this function is often extremely compact, implicitly grouping together states that agree on value at different points in the dynamic programming computation. As such, the number of expected value computations and maximizations required by dynamic programming are greatly reduced. SPUDD was applied to the IPPC instances using a timer that allowed value iteration to run until the timeout was exceeded. The timer was dynamically set to be the remaining time in the competition divided by the number of remaining instances. The instances were solved in order of difficulty level. The traffic domain was removed after the second set of instances was attempted, as the space usage went beyond the available memory.