Abstract. A common hypothesis in multi-agent systems (MAS) literature is that decentralized MAS are better at coping with dynamic and large scale problems compared to centralized algorithms. Existing work investigates this hypothesis in a limited way, often with no support for further evaluation, slowing down the advance of more general conclusions. Investigating this hypothesis more systematically is time consuming as it requires four main components: 1) formal metrics for the variables of interest, 2) a problem instance generator using these metrics, 3) (de)centralized algorithms and 4) a simulation platform that facilitates the execution of these algorithms. Present paper describes the construction of an instance generator based on previously established formal metrics and simulation platform with support for (de)centralized algorithms. Using our instance generator, a benchmark logistics dataset with varying levels of dynamism and scale is created and we demonstrate how it can be us...
Rinde R. S. van Lon, Tom Holvoet