This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Abstract-- In robot deployment problems, the fundamental issue is to optimize a steady state performance measure that depends on the spatial configuration of a group of robots. For...
This paper is concerned with developing an information-theoretic framework to aggregate the state space of a Hidden Markov Model (HMM) on discrete state and observation spaces. The...
This paper reports on steps that have been taken to enhance previously presented evolutionary sound matching work. In doing so, the convergence characteristics are shown to provide...
In this paper, we address the rate control problem for layered multicast traffic, with the objective of solving a generalized throughput/fairness objective. Our approach is based o...