Asynchronous Communication Aware Multi-Agent Task Allocation

Multi-agent task allocation in physical environments with spatial and temporal constraints are hard problems relevant to many realistic applications. A task allocation algorithm based on Fisher market clearing (FMC_TA), which can be performed centrally or distributively, has been shown to produce high quality allocations compared to the centralized and distributed state of the art incomplete optimization algorithms. However, the algorithm is synchronous and thus depends on perfect communication between agents. We propose FMC_ATA, an asynchronous version of FMC_TA, which is robust to message latency and message loss. In contrast to the former version of the algorithm, FMC_ATA allows agents to identify events and initiate the generation of an updated allocation. Thus, it is more compatible with dynamic environments.