Jonathan D. Thomas

According to our database, Jonathan D. Thomas authored at least 13 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

PACE: Procedural Abstractions for Communicating Efficiently.

Jonathan D. Thomas, Andrea Silvi, Devdatt P. Dubhashi, Moa Johansson

Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

Learning Efficient Recursive Numeral Systems via Reinforcement Learning.

Andrea Silvi, Jonathan D. Thomas, Emil Carlsson, Devdatt P. Dubhashi, Moa Johansson

Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

2024

ACE: Abstractions for Communicating Efficiently.

Jonathan D. Thomas, Andrea Silvi, Devdatt P. Dubhashi, Vikas Garg, Moa Johansson

CoRR, 2024

Scalable Multi-Agent Reinforcement Learning for Warehouse Logistics with Robotic and Human Co-Workers.

Aleksandar Krnjaic, Raul D. Steleac, Jonathan D. Thomas, Georgios Papoudakis, Lukas Schäfer, Andrew Wing-Keung To, Kuan-Ho Lao, Murat Cubuktepe, Matthew Haley, Peter Börsting, Stefano V. Albrecht

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

2023

Multi-lingual agents through multi-headed neural networks.

Jonathan D. Thomas, Raúl Santos-Rodríguez, Mihai Anca, Robert J. Piechocki

Proceedings of the 2023 Northern Lights Deep Learning Workshop, 2023

Achieving Goals Using Reward Shaping and Curriculum Learning.

Mihai Anca, Jonathan D. Thomas, Dabal Pedamonti, Mark Hansen, Matthew Studley

Proceedings of the Future Technologies Conference, 2023

2022

Scalable Multi-Agent Reinforcement Learning for Warehouse Logistics with Robotic and Human Co-Workers.

Aleksandar Krnjaic, Jonathan D. Thomas, Georgios Papoudakis, Lukas Schäfer, Peter Börsting, Stefano V. Albrecht

CoRR, 2022

Sim2real for Reinforcement Learning Driven Next Generation Networks.

Peizheng Li, Jonathan D. Thomas, Xiaoyang Wang, Hakan Erdol, Abdelrahim Kasem Ahmad, Rui Inacio, Shipra Kapoor, Arjun Parekh, Angela Doufexi, Arman Shojaeifard, Robert J. Piechocki

CoRR, 2022

Effects of Reward Shaping on Curriculum Learning in Goal Conditioned Tasks.

Mihai Anca, Matthew Studley, Mark Hansen, Jonathan D. Thomas, Dabal Pedamonti

CoRR, 2022

Self-play learning strategies for resource assignment in Open-RAN networks.

Xiaoyang Wang, Jonathan D. Thomas, Robert J. Piechocki, Shipra Kapoor, Raúl Santos-Rodríguez, Arjun Parekh

Comput. Networks, 2022

RLOps: Development Life-Cycle of Reinforcement Learning Aided Open RAN.

Peizheng Li, Jonathan D. Thomas, Xiaoyang Wang, Ahmed Khalil, Abdelrahim Kasem Ahmad, Rui Inacio, Shipra Kapoor, Arjun Parekh, Angela Doufexi, Arman Shojaeifard, Robert J. Piechocki

IEEE Access, 2022

Federated Meta-Learning for Traffic Steering in O-RAN.

Hakan Erdol, Xiaoyang Wang, Peizheng Li, Jonathan D. Thomas, Robert J. Piechocki, George Oikonomou, Rui Inacio, Abdelrahim Kasem Ahmad, Keith Briggs, Shipra Kapoor

Proceedings of the 96th Vehicular Technology Conference, 2022

2021

Network Maintenance Planning Via Multi-Agent Reinforcement Learning.

Jonathan D. Thomas, Marco Pérez-Hernández, Ajith Kumar Parlikad, Robert J. Piechocki

Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics, 2021