Ryan Kortvelesy

According to our database, Ryan Kortvelesy authored at least 12 papers between 2021 and 2024.

Collaborative distances:

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

2024

Revisiting Recurrent Reinforcement Learning with Memory Monoids.

Steven D. Morad, Chris Lu, Ryan Kortvelesy, Stephan Liwicki, Jakob N. Foerster, Amanda Prorok

CoRR, 2024

2023

Modeling Aggregate Downwash Forces for Dense Multirotor Flight.

Jennifer Gielis, Ajay Shankar, Ryan Kortvelesy, Amanda Prorok

CoRR, 2023

Fixed Integral Neural Networks.

Ryan Kortvelesy

CoRR, 2023

Reinforcement Learning with Fast and Forgetful Memory.

Steven D. Morad, Ryan Kortvelesy, Stephan Liwicki, Amanda Prorok

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Generalised f-Mean Aggregation for Graph Neural Networks.

Ryan Kortvelesy, Steven D. Morad, Amanda Prorok

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

POPGym: Benchmarking Partially Observable Reinforcement Learning.

Steven D. Morad, Ryan Kortvelesy, Matteo Bettini, Stephan Liwicki, Amanda Prorok

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Permutation-Invariant Set Autoencoders with Fixed-Size Embeddings for Multi-Agent Learning.

Ryan Kortvelesy, Steven D. Morad, Amanda Prorok

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

QGNN: Value Function Factorisation with Graph Neural Networks.

Ryan Kortvelesy, Amanda Prorok

CoRR, 2022

Modeling Partially Observable Systems using Graph-Based Memory and Topological Priors.

Steven D. Morad, Stephan Liwicki, Ryan Kortvelesy, Roberto Mecca, Amanda Prorok

Proceedings of the Learning for Dynamics and Control Conference, 2022

VMAS: A Vectorized Multi-agent Simulator for Collective Robot Learning.

Matteo Bettini, Ryan Kortvelesy, Jan Blumenkamp, Amanda Prorok

Proceedings of the Distributed Autonomous Robotic Systems - 16th International Symposium, 2022

The Holy Grail of Multi-Robot Planning: Learning to Generate Online-Scalable Solutions from Offline-Optimal Experts.

Amanda Prorok, Jan Blumenkamp, Qingbiao Li, Ryan Kortvelesy, Zhe Liu, Ethan Stump

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021

ModGNN: Expert Policy Approximation in Multi-Agent Systems with a Modular Graph Neural Network Architecture.

Ryan Kortvelesy, Amanda Prorok

Proceedings of the IEEE International Conference on Robotics and Automation, 2021