Deep-layer machine learning architectures continue to emerge as a promising biologically-inspired framework for achieving scalable perception in artificial agents. State inference ...
As computer systems continue to grow in power and access more networked content and services, we believe there will be an increasing need to provide more user-centric systems that...
It is crucial for embedded systems to adapt to the dynamics of open environments. This adaptation process becomes especially challenging in the context of multiagent systems. In t...
We present a dynamic and distributed approach to the hospital patient scheduling problem: the multi-agent Pareto-improvement appointment exchanging algorithm, MPAEX. It respects t...
Ivan B. Vermeulen, Sander M. Bohte, D. J. A. Somef...
Several researchers, present authors included, envision personal mobile robot agents that can assist humans in their daily tasks. Despite many advances in robotics, such mobile ro...
Stephanie Rosenthal, Joydeep Biswas, Manuela M. Ve...