The ability for an agent to reason under uncertainty is crucial for many planning applications, since an agent rarely has access to complete, error-free information about its envi...
Multiagent Partially Observable Markov Decision Processes are a popular model of multiagent systems with uncertainty. Since the computational cost for finding an optimal joint pol...
In the past, partial order reduction has been used successfully to combat the state explosion problem in the context of model checking for non-probabilistic systems. For both line...
Christel Baier, Pedro R. D'Argenio, Marcus Grö...
In this work, we explore how local interactions can simplify the process of decision-making in multiagent systems, particularly in multirobot problems. We review a recent decision-...