4 papers
Deterministic Policy Gradient for Reinforcement Learning with Continuous Time and State
Ziheng Cheng, Xin Guo, Yufei Zhang
The theory of continuous-time reinforcement learning (RL) has progressed rapidly in recent years. While the ultimate objective of RL is typically to learn deterministic control pol…
Distributed games with jumps: An -potential game approach
Xin Guo, Xinyu Li, Yufei Zhang
Motivated by game-theoretic models of crowd motion dynamics, this paper analyzes a broad class of distributed games with jump diffusions within the recently developed -potential…
BSDE Approach for -Potential Stochastic Differential Games
Xin Guo, Xun Li, Liangquan Zhang
In this paper, we examine a class of -potential stochastic differential games with random coefficients via the backward stochastic differential equations (BSDEs) approach. Speci…
Nonstationary nonzero-sum Markov games under a probability criterion
Xin Guo, Xin Wen
This paper deals with N-person nonzero-sum discrete-time Markov games under a probability criterion, in which the transition probabilities and reward functions are allowed to vary…