Although well understood in the single-agent framework, the use of traditional reinforcement learning (RL) algorithms in multi-agent systems (MAS) is not always justified. The fe...
This paper introduces a methodology to help the programmer in the transition from a set of desired global properties expressed as an equation-based model (EBM) that a Multi-Agent ...
In Multi-Agent learning, agents must learn to select actions that maximize their utility given the action choices of the other agents. Cooperative Coevolution offers a way to evol...
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
Building multi-agent systems that can scale up to very large number of agents is a challenging research problem. In this paper, we present Distributed Multi Agent System Framework...
I. V. Aprameya Rao, Manish Jain, Kamalakar Karlapa...