In this paper we evaluate Probability Collectives (PC) as a framework for the coordination of collectives of agents. PC allows for efficient multiagent coordination without the need of explicit acquaintance models. We selected Distributed Constraint Satisfaction as case study to evaluate the PC approach for the well-known 8-Queens problem. Two different architectural structures have been implemented, one centralized and one decentralized. We have also compared between the decentralized version of PC and ADOPT, the state of the art in distributed constraint satisfaction algorithms.
['Matteo Vasirani', 'Sascha Ossowski']
Collective-Based Multiagent Coordination: A Case Study