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...
Making a truly useful massively multi-agent system is difficult since the actions of the full ensemble of agents cannot be controlled by designing just one agent. It is critical ...
Abstract. Taxonomies in the area of Multi-Agent Systems (MAS) classify problems according to the underlying principles and assumptions of the agents’ abilities, rationality and i...
This paper defines an approach to simulation of natural systems, inspired by complex systems theory. A complex natural system is modeled as a multi-agent simulation system, agents...
This study concerns virtual environments for training in operational conditions. The principal developed idea is that these environments are heterogeneous and open multi-agent sys...
Cedric Buche, Ronan Querrec, Pierre De Loor, Pierr...