  Temporal logic based synthesis approaches are often used to find trajectories
that are correct-by-construction for tasks in systems with complex behavior.
Some examples of such tasks include synchronization for multi-agent hybrid
systems, reactive motion planning for robots. However, the scalability of such
approaches is of concern and at times a bottleneck when transitioning from
theory to practice. In this paper, we identify a class of problems in the GR(1)
fragment of linear-time temporal logic (LTL) where the synthesis problem allows
for a decomposition that enables easy parallelization. This decomposition also
reduces the alternation depth, resulting in more efficient synthesis. A
multi-agent robot gridworld example with coordination tasks is presented to
demonstrate the application of the developed ideas and also to perform
empirical analysis for benchmarking the decomposition-based synthesis approach.
