Experimental analysis of networks of cooperative learning agents (to verify certain properties such as the system's stability) has been commonly used due to the complexity of...
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...
Recent advances in technology allow multi-agent systems to be deployed in cooperation with or as a service for humans. Typically, those systems are designed assuming individually ...
The Multi-Agent Coordination and Control (MACC) testbed is a modelling and simulation environment for manufacturing control. It provides benefits to both the research community an...
Paul Verstraete, Paul Valckenaers, Hendrik Van Bru...
This paper describes the design and implementation of robotic agents for the RoboCup Simulation 2D category that learns using a recently proposed Heuristic Reinforcement Learning a...
Luiz A. Celiberto, Carlos H. C. Ribeiro, Anna Hele...