Ryan Kortvelesy

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 20

Top Topics

Reinforcement Learning

Partially Observable

Top Venues

Publications

Steven D. Morad, Chris Lu, Ryan Kortvelesy, Stephan Liwicki, Jakob N. Foerster, Amanda Prorok
Revisiting Recurrent Reinforcement Learning with Memory Monoids. CoRR (2024)
Matteo Bettini, Ryan Kortvelesy, Amanda Prorok
Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning. CoRR (2024)
Steven D. Morad, Ryan Kortvelesy, Matteo Bettini, Stephan Liwicki, Amanda Prorok
POPGym: Benchmarking Partially Observable Reinforcement Learning. CoRR (2023)
Ryan Kortvelesy
Fixed Integral Neural Networks. CoRR (2023)
Steven D. Morad, Ryan Kortvelesy, Stephan Liwicki, Amanda Prorok
Reinforcement Learning with Fast and Forgetful Memory. NeurIPS (2023)
Ryan Kortvelesy, Steven D. Morad, Amanda Prorok
Permutation-Invariant Set Autoencoders with Fixed-Size Embeddings for Multi-Agent Learning. CoRR (2023)
Ryan Kortvelesy, Steven D. Morad, Amanda Prorok
Permutation-Invariant Set Autoencoders with Fixed-Size Embeddings for Multi-Agent Learning. AAMAS (2023)
Steven D. Morad, Ryan Kortvelesy, Stephan Liwicki, Amanda Prorok
Reinforcement Learning with Fast and Forgetful Memory. CoRR (2023)
Jennifer Gielis, Ajay Shankar, Ryan Kortvelesy, Amanda Prorok
Modeling Aggregate Downwash Forces for Dense Multirotor Flight. CoRR (2023)
Ryan Kortvelesy, Steven D. Morad, Amanda Prorok
Generalised f-Mean Aggregation for Graph Neural Networks. NeurIPS (2023)
Steven D. Morad, Ryan Kortvelesy, Matteo Bettini, Stephan Liwicki, Amanda Prorok
POPGym: Benchmarking Partially Observable Reinforcement Learning. ICLR (2023)
Ryan Kortvelesy, Steven D. Morad, Amanda Prorok
Generalised f-Mean Aggregation for Graph Neural Networks. CoRR (2023)
Ryan Kortvelesy, Amanda Prorok
QGNN: Value Function Factorisation with Graph Neural Networks. CoRR (2022)
Amanda Prorok, Jan Blumenkamp, Qingbiao Li, Ryan Kortvelesy, Zhe Liu, Ethan Stump
The Holy Grail of Multi-Robot Planning: Learning to Generate Online-Scalable Solutions from Offline-Optimal Experts. AAMAS (2022)
Steven D. Morad, Stephan Liwicki, Ryan Kortvelesy, Roberto Mecca, Amanda Prorok
Modeling Partially Observable Systems using Graph-Based Memory and Topological Priors. L4DC (2022)
Matteo Bettini, Ryan Kortvelesy, Jan Blumenkamp, Amanda Prorok
VMAS: A Vectorized Multi-agent Simulator for Collective Robot Learning. DARS (2022)
Matteo Bettini, Ryan Kortvelesy, Jan Blumenkamp, Amanda Prorok
VMAS: A Vectorized Multi-Agent Simulator for Collective Robot Learning. CoRR (2022)
Amanda Prorok, Jan Blumenkamp, Qingbiao Li, Ryan Kortvelesy, Zhe Liu, Ethan Stump
The Holy Grail of Multi-Robot Planning: Learning to Generate Online-Scalable Solutions from Offline-Optimal Experts. CoRR (2021)
Ryan Kortvelesy, Amanda Prorok
ModGNN: Expert Policy Approximation in Multi-Agent Systems with a Modular Graph Neural Network Architecture. ICRA (2021)
Ryan Kortvelesy, Amanda Prorok
ModGNN: Expert Policy Approximation in Multi-Agent Systems with a Modular Graph Neural Network Architecture. CoRR (2021)