The Monte-Carlo Tree Search algorithm has been successfully applied in various domains. However, its performance heavily depends on the Monte-Carlo part. In this paper, we propose a generic way of improving the Monte-Carlo simulations by using RAVE values, which already strongly improved the tree part of the algorithm. We prove the generality and efficiency of our approach by showing improvemen...

We present a versatile Monte Carlo method for estimating multidimensional integrals, with applications to rare-event probability estimation. The method fuses two distinct and popular Monte Carlo simulation methods — Markov chain Monte Carlo and importance sampling — into a single algorithm. We show that for some illustrative and applied numerical examples the proposed Markov Chain importance sa...

In this paper we deal with performance analysis of Monte Carlo algorithm for large linear algebra problems. We consider applicability and efficiency of the Markov chain Monte Carlo for large problems, i.e., problems involving matrices with a number of non-zero elements ranging between one million and one billion. We are concentrating on analysis of the almost Optimal Monte Carlo (MAO) algorithm...

Monte Carlo Tree Search is a recent algorithm that achieves more and more successes in various domains. We propose an improvement of the Monte Carlo part of the algorithm by modifying the simulations depending on the context. The modification is based on a reward function learned on a tiling of the space of Monte Carlo simulations. The tiling is done by regrouping the Monte Carlo simulations wh...

The use of " event-based " algorithms for particle transport Monte Carlo methods has allowed the successful adaptation of these methods to vector supercomputers. An alternative algorithm for the specific application of photon transport in an axisymmetric inertially confined fusion plasma has been developed and implemented on a vector supercomputer. The new algorithm is described; its unique fea...

In high-intensity (> 1021Wcm−2) laser-matter interactions gamma-ray photon emission by the electrons can strongly effect the electron’s dynamics and copious numbers of electron-positron pairs can be produced by the emitted photons. We show how these processes can be included in simulations by coupling a Monte-Carlo algorithm describing the emission to a particle-in-cell code. The Monte-Carlo al...

In this paper, Multi-Microgrids (MMG) are considered as future smart distribution grids, in which small scale energy resources (SSER) are main power generation units with small scales. Optimal operation of microgrids in defined intervals is carried out to achieve economic conditions in distribution systems. The defined operating problem is optimized using a heuristic algorithm considering uncer...

One of the most challenging issues in multi-objective problems is finding Pareto optimal points. This paper describes an algorithm based on Benders Decomposition Algorithm (BDA) which tries to find Pareto solutions. For this aim, a multi-objective facility location allocation model is proposed. In this case, an integrated BDA and epsilon constraint method are proposed and it is shown that how P...