A major challenge in the field of Multi-Agent Systems is to enable autonomous agents to allocate tasks efficiently. This paper extends previous work on an approach to the collec...
Christian Guttmann, Iyad Rahwan, Michael P. George...
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in largescale systems. In this work, we develop an organization-b...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
In this paper, we show how the dynamics of Q-learning can be visualized and analyzed from a perspective of Evolutionary Dynamics (ED). More specifically, we show how ED can be use...
This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcemen...