Large systems of agents deployed in a real-world environment face threats to their problem solving performance that are independent of the complexity of the problem or the charact...
In this contribution we present a theoretical approach which has been utilized to inform the coordination of the development of complex systems. Coordination is regarded as a form...
Cyclic coordinate descent is a classic optimization method that has witnessed a resurgence of interest in machine learning. Reasons for this include its simplicity, speed and stab...
Abstract. Applying multi-agent systems in real world scenarios requires several essential research questions to be answered. Agents have to perceive their environment in order to t...
Frans C. A. Groen, Matthijs T. J. Spaan, Jelle R. ...
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...