MRCC: A multi-resolution cooperative control agent architecture

The cooperation problem in a complex robotic environment requires the use of explicit mechanisms and control architectures specifically designed to manage the cooperation. Powerful ways of structuring cooperation complexity are required, including models, methodologies, software architectures, information systems and frameworks. In this paper the intentional cooperation control model MRCC, Multi-Resolution Cooperation Control is presented; in particular, the internal agent architecture is studied in detail. The model takes advantage of the Multi Agent Systems (MAS) benefits in order to provide an integral and flexible architecture. The main idea of the MRCC model is based on a hierarchical decomposition of the MAS cooperative control, where each layer manages the decisions at different granularity and abstraction levels. Higher levels take into account general aspects of the system control and generate influences over lower ones. Lower levels manage negotiation mechanism to achieve cooperative actions and control of individual agents. The internal agent architecture is built using a concurrent approach, where several behaviors interact to integrate in a coherent way the operation and contribution of the different MRCC levels. The preliminary simulation results demonstrate that the model can be applied in different multi robot tasks.