Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
This paper investigates the use of reinforcement learning in electric power system emergency control. The approach consists of using numerical simulations together with on-policy M...
The two most important tasks in information extraction from the Web are webpage structure understanding and natural language sentences processing. However, little work has been don...
Chunyu Yang, Yong Cao, Zaiqing Nie, Jie Zhou, Ji-R...
On Navy ships, technological developments enable crews to work more efficiently and effectively. However, in such complex, autonomous, and information-rich environments a competiti...
This paper argues that it is important to study issues concerning trust and reliance when developing systems that are intended to augment cognition. Operators often under-rely on t...
Peter-Paul van Maanen, Tomas Klos, Kees van Dongen