paths as when solving single-agent pathfinding problems, and then it adds constraints in an incremental way in order to avoid collisions. Constraints programming: with this kind of approach, MAPF problems are transformed into a set of constraints and then solved using specific constraint solvers such as SAT and Mixed Integer Programming (MIP) solvers. Bounded Suboptimal MAPF Solvers Bounded suboptimal algorithms offer a trade-off between the optimality and the cost of the solution. They are said to be bounded by a certain factor because they return solutions with a cost at most equal to the optimal solution cost times the factor. MAPF bounded suboptimal solvers can be divided following the same categorization presented for optimal MAPF solvers. Variations The way in which MAPF problems are defined allows to change various aspects, for example the fact of being in a grid environment or the assumption that time is discrete. This section reports some variations of the classical MAPF problem. Anonymous MAPF It is a version of MAPF in which there is a set of target locations but agents are not assigned a specific target. It does not matter whether the agent that reaches the target, the important thing is that targets are completed. A slight modification of this version is the one in which agents are divided into groups and each group has to perform a set of targets. Multi-Agent Pick-up and Delivery MAPF problem is not able to capture some aspects relative to real world applications. For example, in automated warehouses it happens that robots have to complete several tasks one after the other. For this reason, an extended MAPF version is proposed, called Multi-Agent Pick-up and Delivery (MAPD). In a MAPD setting, agents have to complete a stream of tasks, where each task is composed by a pick-up a location and a delivery location. When planning for the completion of a task, the path has to start from the current position of the robot and to end in the delivery position of the task, passing through the pick-up point. MAPD is considered a "lifelong" version of MAPF in which tasks arrive incrementally. Beyond Classical MAPF The assumptions that the agents are in a grid environment, that their speed is constant and that time is discrete are simplifying hypotheses. Many works take into account the kinematic constraints of agents, such as velocity and orientation, or go past the assumption that the