Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
Building agents for a scenario such as the RoboCup simulation league requires not only methodologies for implementing high-level complex behavior, but also the careful and efficien...
Team decision making under stress involving multiple contexts is an extremely challenging issue faced by various real world application domains. This research is targeted at coupl...
Xiaocong Fan, Bingjun Sun, Shuang Sun, Michael D. ...
This paper presents an agent strategy for complex bilateral negotiations over many issues with inter-dependent valuations. We use ideas inspired by graph theory and probabilistic ...
Valentin Robu, D. J. A. Somefun, Johannes A. La Po...
The increasing number of competitors and the growing traffic demand are the main factors pushing for a more dynamic and flexible service demand allocation mechanism. Human interac...