Multi-Agent Systems in many engineering applications are composed of multiple interacting manned and/or unmanned systems and these agents can be at least partially independent, but no agent has a global view. In practice, human-based resource allocation of multi-agent systems usually results in ad hoc solutions for small-scale quasi-static problems. The project aims at developing the technological foundations on Dynamic Allocation for Large-Scale Multi-Agent Systems for enhancing the automation level and improving the system performance in the face of multiple system level constraints. In this project, computational algorithms for Multi-Objective Optimization Problem will be developed and validated by adopting the Model-Based Systems Engineering (MBSE) for large-scale systems emerged in Smart City applications. The developed technologies can enable industrial customers on deploying many more manned and/or unmanned systems for sophisticated tasks in Smart City applications.
