This paper extends the framework of partially observable Markov decision processes (POMDPs) to multi-agent settings by incorporating the notion of agent models into the state spac...
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are evolving as a popular approach for modeling multiagent systems, and many different algorithms ha...
Abstract. The intent of this position paper is to present the focus of interest of our end-user development (EUD) related research at SAP Research CEC Darmstadt, enabling other par...
In self-adaptive systems, metadata about resources in the system (e.g., services, nodes) must be dynamically published, updated, and discarded. Current adaptive middleware approach...
Johannes Oudenstad, Romain Rouvoy, Frank Eliassen,...
Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...