Abstract. The paradigms of service-oriented computing and modeldriven development are becoming of increasing importance in the field of software engineering. According to these par...
Natallia Kokash, Christian Krause, Erik P. de Vink
Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
A component is the basic re-usable unit of composition to build composite systems by connecting to others through their provided and required ports. Checking the functional complia...
This paper presents the Mitosis framework, which is a combined hardware-software approach to speculative multithreading, even in the presence of frequent dependences among threads....
A gradient-based method for both symmetric and asymmetric multiagent reinforcement learning is introduced in this paper. Symmetric multiagent reinforcement learning addresses the ...