We revisit the problem of supertasking in Pfair-scheduled multiprocessor systems. In this approach, a set of tasks, called component tasks, is assigned to a server task, called a ...
Reinforcement learning (RL) is one of the machine learning techniques and has been received much attention as a new self-adaptive controller for various systems. The RL agent auto...
A novel approach for sensor planning, which incorporates multi-objective optimization principals into the autonomous design of sensing strategies, is presented. The study addresses...
We address the problem of constructing multiagent systems by coordinating heterogeneous, autonomous agents, whose internal designs may not be fully known. A major application area...
Transfer learning addresses the problem of how to leverage knowledge acquired in a source domain to improve the accuracy and speed of learning in a related target domain. This pap...
Lilyana Mihalkova, Tuyen N. Huynh, Raymond J. Moon...