2018
Deep Reinforcement Learning of Marked Temporal Point Processes
NeurIPS 2018poster
In a wide variety of applications, humans interact with a complex environment by means of asynchronous stochastic discrete events in continuous time. Can we design online interventions that will help humans achieve certain goals in such asynchronous setting? In this paper, we address the above probl…