20 citations · 57 across the 19 of their papers we have counts for
6 papers · 1 filter
The microstructure of information through mean field learning interaction
Panagiotis E. Souganidis, Renyuan Xu, Thaleia Zariphopoulou
We study how knowledge about partially observable model parameters is being created and propagated in large scale systems. Information is generated from observational signals whose…
On the optimal portfolio problem with partial information and related mean field games with relative performance criteria
Panagiotis Souganidis, Thaleia Zariphopoulou
We study optimal portfolio choice models in markets with partial information about the stock's drift. We solve the single agent problem for general utilities using a new approach t…
Decision Making under Costly Sequential Information Acquisition: the Paradigm of Reversible and Irreversible Decisions
Renyuan Xu, Thaleia Zariphopoulou, Luhao Zhang
Decision making in modern stochastic systems, including e-commerce platforms, financial markets and healthcare systems, has evolved into a multifaceted process that combines inform…
Entropy Regularization for Mean Field Games with Learning
Xin Guo, Renyuan Xu, Thaleia Zariphopoulou
Entropy regularization has been extensively adopted to improve the efficiency, the stability, and the convergence of algorithms in reinforcement learning. This paper analyzes both…
Exploration versus exploitation in reinforcement learning: a stochastic control approach
Haoran Wang, Thaleia Zariphopoulou, Xunyu Zhou
We consider reinforcement learning (RL) in continuous time and study the problem of achieving the best trade-off between exploration of a black box environment and exploitation of…
An approximation scheme for semilinear parabolic PDEs with convex and coercive Hamiltonians
Shuo Huang, Gechun Liang, Thaleia Zariphopoulou
We propose an approximation scheme for a class of semilinear parabolic equations that are convex and coercive in their gradients. Such equations arise often in pricing and portfoli…