14 citations · 21 across the 5 of their papers we have counts for
3 papers · 1 filter
Constrained Combinatorial Optimization with Reinforcement Learning
Ruben Solozabal, Josu Ceberio, Martin Takáč
This paper presents a framework to tackle constrained combinatorial optimization problems using deep Reinforcement Learning (RL). To this end, we extend the Neural Combinatorial Op…
FD-Net with Auxiliary Time Steps: Fast Prediction of PDEs using Hessian-Free Trust-Region Methods
Nur Sila Gulgec, Zheng Shi, Neil Deshmukh +2
Discovering the underlying physical behavior of complex systems is a crucial, but less well-understood topic in many engineering disciplines. This study proposes a finite-differenc…
A Layered Architecture for Active Perception: Image Classification using Deep Reinforcement Learning
Hossein K. Mousavi, Guangyi Liu, Weihang Yuan +3
We propose a planning and perception mechanism for a robot (agent), that can only observe the underlying environment partially, in order to solve an image classification problem. A…