Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
Previous studies have demonstrated that encoding a Bayesian network into a SAT formula and then performing weighted model counting using a backtracking search algorithm can be an ...
A main idea underlying bounded model checking is to limit the length of the potential counter-examples, and then prove properties for the bounded version of the problem. In softwar...
: This paper addresses the dynamic pricing problem of a single-item, make-to-stock production system. Demand arrives according to Poisson processes with changeable arrival rate dep...
—We investigate location distinction, the ability of a receiver to determine when a transmitter has changed location, which has application for energy conservation in wireless se...