A gradient-based method for both symmetric and asymmetric multiagent reinforcement learning is introduced in this paper. Symmetric multiagent reinforcement learning addresses the ...
Maximum Likelihood estimation theory can be used to develop optimal timing recovery schemes for digital communication systems. Tunable digital interpolation filters are commonly ...
We propose a Bayesian extension to the ad-hoc Language Model. Many smoothed estimators used for the multinomial query model in ad-hoc Language Models (including Laplace and Bayes-...
Hugo Zaragoza, Djoerd Hiemstra, Michael E. Tipping
Simple retrenchment is briefly reviewed in the B language of J.-R. Abrial [1] as a liberalisation of classical refinement, for the formal description of application developments ...
The provision of Quality of Service (QoS) in a seamless way over the dominating internetworking protocol of our times (IP), has been a challenge for many researchers in the past ye...