In this paper, a novel and effective criterion based on the estimation of the signal-to-noise-ratio figure (SNRF) is proposed to optimize the number of hidden neurons in neural ne...
We propose the energy efficient MAC algorithm in this paper. In the proposed algorithm, each node sets the contention window size with respect to the residual energy, the harvest...
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...
Distributed optimal traffic engineering in the presence of multiple paths has been found to be a difficult problem to solve. In this paper, we introduce a new approach in an attem...
Intelligent agents often need to assess user utility functions in order to make decisions on their behalf, or predict their behavior. When uncertainty exists over the precise natu...