UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Constrained Q-Learning for Batch Process Optimization

Pan, E; Petsagkourakis, P; Mowbray, M; Zhang, D; del Rio-Chanona, A; (2021) Constrained Q-Learning for Batch Process Optimization. In: Proceedings of Challenges of Real-World Reinforcement Learning Workshop at the 34th Conference on Neural Information Processing Systems (NeurIPS 2020). NeurIPS: Vancouver, Canada.. Green open access

[thumbnail of 40_CameraReady_NeurIPS_RWRL_Constrained_Q_Learning_updated.pdf]
Preview
Text
40_CameraReady_NeurIPS_RWRL_Constrained_Q_Learning_updated.pdf - Published Version

Download (1MB) | Preview
Type: Proceedings paper
Title: Constrained Q-Learning for Batch Process Optimization
Event: Challenges of Real-World Reinforcement Learning Workshop at the 34th Conference on Neural Information Processing Systems (NeurIPS 2020)
Open access status: An open access version is available from UCL Discovery
Publisher version: https://sites.google.com/view/neurips2020rwrl
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering
URI: https://discovery.ucl.ac.uk/id/eprint/10119664
Downloads since deposit
75Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item