Coordination in multiagent reinforcement learning systems by virtual reinforcement signals

A Multiagent Reinforcement Learning algorithm to solve the Community Detection Problem

Community detection is a challenging optimization problem that consists of searching for communities that belong to a network under the assumption that the nodes of the same community share properties that enable the detection of new characteristics or functional relationships in the network. Although there are many algorithms developed for community detection, most of them are unsuitable when ...

Hierarchical Neuro-Fuzzy with a market-driven coordination mechanism (MA-RL-HNFP- MD) and a MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with graph

This paper presents the research and development of a hybrid neuro-fuzzy model for the hierarchical coordination of multiple intelligent agents. The main objective of the models is to have multiple agents interact intelligently with each other in complex systems. We developed two new models of coordination for intelligent neuro-fuzzy multiagent systems that use MultiAgent Reinforcement Learning...

Multiagent Coordination in Cooperative Q-learning Systems

Many reinforcement learning architectures fail to learn optimal group behaviors in the multiagent domain. Although these coordination difficulties are often attributed to the non-Markovian environment created by the gradually-changing policies of concurrently learning agents, a careful analysis of the situation reveals an underlying problem structure which can cause suboptimal group policies ev...

Improving on the reinforcement learning of coordination in cooperative multi-agent systems

We report on an investigation of reinforcement learning techniques for the learning of coordination in cooperative multiagent systems. These techniques are variants of Q-learning (Watkins, 1989) that are applicable to scenarios where mutual observation of actions is not possible. To date, reinforcement learning approaches for such independent agents did not guarantee convergence to the optimal ...

Multiagent Reinforcement Learning and Coordination for Urban Traffic Control using Coordination Graphs and Max-plus Master’s Thesis Artificial Intelligence Specialization Intelligent Systems