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...
In this contribution we analyze communication requirements of multi-agent simulation systems using ITSimBw – developed at Fraunhofer IAIS – as an example. A focus is put on is...
Fault tolerance is an important property of large-scale multiagent systems as the failure rate grows with both the number of the hosts and deployed agents, and the duration of com...
Many real-world tasks can be decomposed into pipelines of sequential operations (where subtasks may themselves be composed of one or more pipelines). JGram is a framework enabling...
Rahul Sukthankar, Antoine Brusseau, Ray Pelletier,...
Abstract. A framework for Multi Agent Data Mining (MADM) is described. The framework comprises a collection of agents cooperating to address given data mining tasks. The fundamenta...
Santhana Chaimontree, Katie Atkinson, Frans Coenen