Search Results for author: Simon Hirländer

Found 2 papers, 0 papers with code

Deep Q-Learning versus Proximal Policy Optimization: Performance Comparison in a Material Sorting Task

no code implementations2 Jun 2023 Reuf Kozlica, Stefan Wegenkittl, Simon Hirländer

This paper presents a comparison between two well-known deep Reinforcement Learning (RL) algorithms: Deep Q-Learning (DQN) and Proximal Policy Optimization (PPO) in a simulated production system.

Q-Learning Reinforcement Learning (RL)

A Modular Test Bed for Reinforcement Learning Incorporation into Industrial Applications

no code implementations2 Jun 2023 Reuf Kozlica, Georg Schäfer, Simon Hirländer, Stefan Wegenkittl

This application paper explores the potential of using reinforcement learning (RL) to address the demands of Industry 4. 0, including shorter time-to-market, mass customization, and batch size one production.

reinforcement-learning Reinforcement Learning (RL)

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