Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
In this paper, we present a new method to calculate reinforcement value in QoS routing algorithm for real-time multimedia based on Ant algorithm to efficiently and effectively rein...
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Most of the current algorithms for finding related pages are exclusively based on text corpora of the WWW or incorporate only authority or hub values of pages. In this paper, we ...
Paul-Alexandru Chirita, Daniel Olmedilla, Wolfgang...
In this paper we investigate the relation between transfer learning in reinforcement learning with function approximation and supervised learning with concept drift. We present a n...