Ryan Kortvelesy

24 papers A* 6A 2Journal 13Unranked 3

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