research
∙
08/11/2023
Learning Control Policies for Variable Objectives from Offline Data
Offline reinforcement learning provides a viable approach to obtain adva...
share
research
∙
06/09/2022
Quantum Policy Iteration via Amplitude Estimation and Grover Search – Towards Quantum Advantage for Reinforcement Learning
We present a full implementation and simulation of a novel quantum reinf...
research
∙
01/14/2022
Comparing Model-free and Model-based Algorithms for Offline Reinforcement Learning
Offline reinforcement learning (RL) Algorithms are often designed with e...
research
∙
08/30/2021
Trustworthy AI for Process Automation on a Chylla-Haase Polymerization Reactor
In this paper, genetic programming reinforcement learning (GPRL) is util...
research
∙
07/12/2021
Behavior Constraining in Weight Space for Offline Reinforcement Learning
In offline reinforcement learning, a policy needs to be learned from a s...
research
∙
07/20/2020
Interpretable Control by Reinforcement Learning
In this paper, three recently introduced reinforcement learning (RL) met...
research
∙
04/29/2018
Generating Interpretable Fuzzy Controllers using Particle Swarm Optimization and Genetic Programming
Autonomously training interpretable control strategies, called policies,...
research
∙
12/12/2017
Interpretable Policies for Reinforcement Learning by Genetic Programming
The search for interpretable reinforcement learning policies is of high ...
research
∙
09/27/2017
A Benchmark Environment Motivated by Industrial Control Problems
In the research area of reinforcement learning (RL), frequently novel an...
research
∙
05/20/2017
Batch Reinforcement Learning on the Industrial Benchmark: First Experiences
The Particle Swarm Optimization Policy (PSO-P) has been recently introdu...
research
∙
10/19/2016