218 citations · 811 across the 15 of their papers we have counts for
3 papers · 1 filter
A review on deep reinforcement learning for fluid mechanics: an update
Jonathan Viquerat, Philippe Meliga, Elie Hachem
In the past couple of years, the interest of the fluid mechanics community for deep reinforcement learning (DRL) techniques has increased at fast pace, leading to a growing bibliog…
Policy Fusion for Adaptive and Customizable Reinforcement Learning Agents
Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov
In this article we study the problem of training intelligent agents using Reinforcement Learning for the purpose of game development. Unlike systems built to replace human players…
Policy-based optimization: single-step policy gradient method seen as an evolution strategy
Jonathan Viquerat, Régis Duvigneau, Philippe Meliga +2
This research reports on the recent development of a black-box optimization method based on single-step deep reinforcement learning (DRL), and on its conceptual proximity to evolut…