Vladimir Samsonov

Orcid: 0000-0003-4147-6470

According to our database1, Vladimir Samsonov authored at least 11 papers between 2019 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2022
Deep Reinforcement Learning for Robotic Control in High-Dexterity Assembly Tasks - A Reward Curriculum Approach.
Int. J. Semantic Comput., 2022

Reinforcement Learning in Manufacturing Control: Baselines, challenges and ways forward.
Eng. Appl. Artif. Intell., 2022

Human-Centric Machine Learning Approach for Injection Mold Design: Towards Automated Ejector Pin Placement.
Proceedings of the Machine Learning, Optimization, and Data Science, 2022

2021
Optimisation of a Workpiece Clamping Position with Reinforcement Learning for Complex Milling Applications.
Proceedings of the Machine Learning, Optimization, and Data Science, 2021

Global Reward Design for Cooperative Agents to Achieve Flexible Production Control under Real-time Constraints.
Proceedings of the 23rd International Conference on Enterprise Information Systems, 2021

Manufacturing Control in Job Shop Environments with Reinforcement Learning.
Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021

2020
Reinforcement Learning for Short-Term Production Scheduling with Sequence-Dependent Setup Waste.
ERCIM News, 2020

Neural Combinatorial Optimization for Production Scheduling with Sequence-Dependent Setup Waste.
Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Using Reinforcement Learning for Optimization of a Workpiece Clamping Position in a Machine Tool.
Proceedings of the 22nd International Conference on Enterprise Information Systems, 2020

2019
More Machine Learning for Less: Comparing Data Generation Strategies in Mechanical Engineering and Manufacturing.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Evaluation and Comparison of Cross-lingual Text Processing Pipelines.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019


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