Reinforcement learning has been used for training game playing agents. The value function for a complex game must be approximated with a continuous function because the number of ...
Converting complex equations into simpler, more tractable equations usually involves approximation. Approximation is usually done by identifying and removing insignificant terms, ...
Abstract. In this work, we address the problem of transient and steadystate analysis of a stochastic Petri net which includes non Markovian distributions with a finite support but ...
State-dependent importance sampling (SDIS) has proved to be particularly useful in simulation (specially in rare event analysis of stochastic systems). One approach for designing ...
Recently, a new domain store for set-variables has been proposed which totally orders all values in the domain of a set-variable based on cardinality and lexicography. Traditionall...
Yuri Malitsky, Meinolf Sellmann, Willem Jan van Ho...