3 papers
cs.LG2026
Reinforcement Learning with Hawkes-Structured Networks for Market Making
Fernando Acero, Philipp Plank, Yufei Zhang
Market making under realistic order-flow dynamics is challenging due to the clustered, self-exciting nature of order arrivals, which are naturally modeled by non-Markovian Hawkes p…
math.OC2026
Learning Distributed Equilibria in Linear-Quadratic Stochastic Differential Games: An -Potential Approach
Philipp Plank, Yufei Zhang
We analyze independent policy-gradient (PG) learning in -player linear-quadratic (LQ) stochastic differential games. Each player employs a distributed policy that depends only o…
math.OC2025
Policy Optimization for Continuous-time Linear-Quadratic Graphon Mean Field Games
Philipp Plank, Yufei Zhang
Multi-agent reinforcement learning, despite its popularity and empirical success, faces significant scalability challenges in large-population dynamic games. Graphon mean field gam…