In this paper, we investigate Reinforcement learning (RL) in multi-agent systems (MAS) from an evolutionary dynamical perspective. Typical for a MAS is that the environment is not ...
Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinke...
Abstract— The most widely applied resource allocation strategy is to balance, or equalize, the total workload assigned to each resource. In mobile multi-agent systems, this princ...
Abstract. Engineering non-trivial open multi-agent systems is a challenging task. Our research focusses on situated multi-agent systems, i.e. systems in which agents are explicitly...
Elke Steegmans, Danny Weyns, Tom Holvoet, Yolande ...
This paper presents DARX, our framework for building applications that provide adaptive fault tolerance. It relies on the fact that multi-agent platforms constitute a very strong ...
In the multi-agent pathfinding problem, groups of agents need to plan paths between their respective start and goal locations in a given environment, usually a two-dimensional map...