We describe the version of the GPT planner to be used in the planning competition. This version, called mGPT, solves mdps specified in the ppddl/nlanguage by extracting and using different classes of lower bounds, along with various heuristic-search /nalgorithms. The lower bounds are extracted from deterministic relaxations of the mdp where alternative/nprobabilistic effects of an action are mapped into different, independent, deterministic actions. The heuristic-search algorithms, on the other hand, use these lower bounds for focusing the updates and delivering a consistent value function over all states reachable from the initial state with the greedy policy.