Background modeling plays an important role in video surveillance, yet in complex scenes it is still a challenging problem. Among many difficulties, problems caused by illuminatio...
In this paper we propose interaction-driven Markov games (IDMGs), a new model for multiagent decision making under uncertainty. IDMGs aim at describing multiagent decision problem...
Reinforcement Learning research is traditionally devoted to solve single-task problems. Therefore, anytime a new task is faced, learning must be restarted from scratch. Recently, ...
To keep a network of enterprises sustainable, inter-organizational control measures are needed to detect or prevent opportunistic behaviour of network participants. We present a m...
Vera Kartseva, Joris Hulstijn, Jaap Gordijn, Yao-H...
The queueing Petri net (QPN) paradigm provides a number of benefits over conventional modeling paradigms such as queueing networks and generalized stochastic Petri nets. Using qu...