Stochastic optimal control and games have a wide range of applications, from finance and
economics to social sciences, robotics, and energy management. Many real-world …

One of the challenges for multiagent reinforcement learning (MARL) is designing efficient
learning algorithms for a large system in which each agent has only limited or partial …

In this study, we investigate the competition among insurers under the mean–variance
criterion. The optimization problems are formulated for finite and infinite insurers. The …

We study mean field portfolio games with random parameters, where each player is
concerned with not only her own wealth, but also relative performance to her competitors …

This paper studies a stochastic utility maximisation game under relative performance
concerns in finite-and infinite-agent settings, where a continuum of agents interact through a …

Graphon games have been introduced to study games with many players who interact
through a weighted graph of interaction. By passing to the limit, a game with a continuum of …

We consider an insurance market consisting of multiple competitive insurers with a mean
field interaction via their terminal wealth under the exponential utility with relative …

This paper studies the robust reinsurance and investment games for competitive insurers.
Model uncertainty is characterized by a class of equivalent probability measures. Each …

In this paper we study a time-inconsistent portfolio optimization problem for competitive
agents with CARA utilities and nonexponential discounting. The utility of each agent …

This paper studies an optimal investment–consumption problem for competitive agents with
exponential or power utilities and a common finite time horizon. Each agent regards the …