Policy evaluation problems in multi-agent reinforcement learning (MARL) have attracted growing interest recently. In this setting, agents collaborate to learn the value of a given policy with private local rewards and jointly observed state-action pairs. However, existing fully decentralized algorithms treat each agent equally, without considering communication structure over network, correspon...

in recent years, in iran and other countries the power systems are going to move toward creating a competition structure for selling and buying electrical energy. these changes and the numerous advantages of dgs have made more incentives to use these kinds of generators than before. therefore, it is necessary to study all aspects of dgs, such as size selection and optimal placement and impact o...

Quantitative risk management (QRM, for short) is very important investors or financial institutions. This paper discusses portfolio selection in fuzzy environments by means of stochastic and methods. Two measures called hierarchical value-at-risk (HFVaR, conditional (HFCVaR, are proposed. And then models established based on the measure HFCVaR.

Advances in grid computing have recently sparkled the research and development of Grid problem solving environments for complex design. Parallelism in the form of distributed computing is a growing trend, particularly so in the analysis and optimization of high-fidelity computationally expensive real world design problems in science and engineering. In this paper, we present a powerful and inex...