Current studies have demonstrated that the representational power of predictive state representations (PSRs) is at least equal to the one of partially observable Markov decision p...
Abdeslam Boularias, Masoumeh T. Izadi, Brahim Chai...
We consider the problem of estimating the policy gradient in Partially Observable Markov Decision Processes (POMDPs) with a special class of policies that are based on Predictive ...
This paper details an essential component of a multi-agent distributed knowledge network system for intrusion detection. We describe a distributed intrusion detection architecture...
Guy G. Helmer, Johnny S. Wong, Vasant Honavar, Les...
- This paper presents a supervised learning based power management framework for a multi-processor system, where a power manager (PM) learns to predict the system performance state...
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...