This paper presents the application of a reinforcement learning (RL) approach for the near-optimal control of a re-entrant line manufacturing (RLM) model. The RL approach utilizes...
We explore an application to the game of Go of a reinforcement learning approach based on a linear evaluation function and large numbers of binary features. This strategy has prov...
This paper proposes a novel Mass Spectrometry data profiling method for ovarian cancer detection based on negative correlation learning (NCL). A modified Smoothed Nonlinear Energy ...
Reinforcement learning (RL) problems constitute an important class of learning and control problems faced by artificial intelligence systems. In these problems, one is faced with ...
We present a method for transferring knowledge learned in one task to a related task. Our problem solvers employ reinforcement learning to acquire a model for one task. We then tra...
Lisa Torrey, Trevor Walker, Jude W. Shavlik, Richa...