In this paper we present analysis and calibration techniques that exploit knowledge about a multi agent society in order to calibrate the system parameters of a corresponding socie...
Constructing comprehensive operational models of intended system behaviour is a complex and costly task. Consequently, practitioners have adopted techniques that support increment...
As agent systems are solving more and more complex tasks in increasingly challenging domains, the systems themselves are becoming more complex too, often compromising their adapti...
The trends and recent changes in logistics lead to complex and partially conflicting requirements on logistic planning and control systems. Due to the lack of efficiency of curren...
Hagen Langer, Jan D. Gehrke, Joachim Hammer, Marti...
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...