  We study the problem of control synthesis for multi-agent systems, to achieve
complex, high-level, long-term goals that are assigned to each agent
individually. As the agents might not be capable of satisfying their respective
goals by themselves, requests for other agents' collaborations are a part of
the task descriptions. Particularly, we consider that the task specification
takes a form of a linear temporal logic formula, which may contain requirements
and constraints on the other agent's behavior. A traditional automata-based
approach to multi-agent strategy synthesis from such specifications builds on
centralized planning for the whole team and thus suffers from extreme
computational demands. In this work, we aim at reducing the computational
complexity by decomposing the strategy synthesis problem into short horizon
planning problems that are solved iteratively, upon the run of the agents. We
discuss the correctness of the solution and find assumptions, under which the
proposed iterative algorithm leads to provable eventual satisfaction of the
desired specifications.

Robotics