3 papers
cs.GT2023
Reinforcement Learning for SBM Graphon Games with Re-Sampling
Peihan Huo, Oscar Peralta, Junyu Guo +2
The Mean-Field approximation is a tractable approach for studying large population dynamics. However, its assumption on homogeneity and universal connections among all agents limit…
math.PR2023
Duration-dependent stochastic fluid processes and solar energy revenue modeling
Hamed Amini, Andreea Minca, Oscar Peralta
We endow the classical stochastic fluid process with a duration-dependent Markovian arrival process (DMArP). We show that this provides a flexible model for the revenue of a solar…
math.PR2023
Ruin Probabilities for Risk Processes in Stochastic Networks
Hamed Amini, Zhongyuan Cao, Andreea Minca +1
We study multidimensional Cramér-Lundberg risk processes where agents, located on a large sparse network, receive losses form their neighbors. To reduce the dimensionality of the p…