We present the development and analysis of a reinforcement learning (RL)...
In this paper, we propose a numerical methodology for finding the closed...
Real-world data can be multimodal distributed, e.g., data describing the...
Stochastic optimal control and games have found a wide range of applicat...
The optimal stopping problem is one of the core problems in financial
ma...
Large scale dynamics of the oceans and the atmosphere are governed by th...
Game theory has been an effective tool in the control of disease spread ...
One of the core problems in mean-field control and mean-field games is t...
Existing deep learning methods for solving mean-field games (MFGs) with
...
This paper concerns the convergence of empirical measures in high dimens...
Stochastic control problems with delay are challenging due to the
path-d...
Game theory has been an effective tool in the control of disease spread ...
Stochastic differential games have been used extensively to model agents...
We propose a deep neural network-based algorithm to identify the Markovi...
In this paper, we apply the idea of fictitious play to design deep neura...
In this paper, we propose deep learning algorithms for ranking response
...
We propose and analyze sequential design methods for the problem of rank...