We present an approach to computing cyclic schedules online and in real time, while attempting to maximize a quality-of-service metric. The motivation is the detection of RF emitt...
— A central challenging problem in humanoid robotics is to plan and execute dynamic tasks in dynamic environments. Given that the environment is known, sampling-based online moti...
In the field of machine translation, automatic metrics have proven quite valuable in system development for tracking progress and measuring the impact of incremental changes. Howe...
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
The authors propose a co-adaptive approach to controlling parameters for coevolution-based learning classifier systems. By taking advantage of the on-line incremental learning capa...