5th IPC in 2004 and 2006 respectively. It extended PDDL2.1 with probabilistic effects (discrete, general probability distributions over possible effects of an action), reward fluents (for incrementing or decrementing the total reward of a plan in the effects of the actions), goal rewards (for rewarding a state-trajectory, which incorporates at least one goal-state), and goal-achieved fluents (which were true, if the state-trajectory incorporated at least one goal-state). Eventually these changes allowed PPDDL1.0 to realize Markov Decision Process (MDP) planning, where there may be uncertainty in the state-transitions, but the environment is fully observable for the planner/agent. APPL APPL (Abstract Plan Preparation Language) is a newer variant of NDDL from 2006, which is more abstract than most existing planning languages such as PDDL or NDDL. The goal of this language was to simplify the formal analysis and specification of planning problems that are intended for safety-critical applications such as power management or automated rendezvous in future manned spacecraft. APPL used the same concepts as NDDL with the extension of actions, and also some other concepts, but still its expressive power is much less than PDDL's (in hope of staying robust and formally verifiable). RDDL RDDL (Relational Dynamic influence Diagram Language) was the official language of the uncertainty track of the 7th IPC in 2011. Conceptually it is based on PPDDL1.0 and PDDL3.0, but practically it is a completely different language both syntactically and semantically. The introduction of partial observability is one of the most important changes in RDDL compared to PPDDL1.0. It allows efficient description of Markov Decision Processes (MDPs) and Partially Observable Markov Decision Processes (POMDPs) by representing everything (state-fluents, observations, actions, ...) with variables. This way RDDL departs from PDDL significantly. Grounded RDDL corresponds to Dynamic Bayesian Networks (DBNs) similarly to PPDDL1.0, but RDDL is more expressive than PPDDL1.0. MA-PDDL MA-PDDL (Multi Agent PDDL) is a minimalistic, modular extension of PDDL3.1 introduced in 2012 (i.e. a new :multi-agent requirement) that allows planning by and for multiple agents. The addition is compatible with all the features of PDDL3.1 and addresses most of the issues of MAPL. It adds the possibility to distinguish between the possibly different actions of different agents (i.e. different capabilities). Similarly different agents may have different goals and/or metrics. The preconditions of actions now may directly refer to concurrent actions (e.g. the actions of other agents) and thus actions with interacting effects can be represented in a