Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
Traffic state estimation is a challenging problem for the transportation community due to the limited deployment of sensing infrastructure. However, recent trends in the mobile pho...
Daniel B. Work, Olli-Pekka Tossavainen, Sebastien ...
We present the Genetic L-System Programming (GLP) paradigm for evolutionary creation and development of parallel rewrite systems (Lsystems, Lindenmayer-systems) which provide a com...
Aging effects, environmental changes, thermal drifts, and soft and hard faults affect physical systems by changing their nature and behavior over time. To cope with a process evolu...
Because of their ability to naturally float in the air, indoor airships (often called blimps) constitute an appealing platform for research in aerial robotics. However, when confr...