Outstanding Paper Award Winners - 2/2 @ RLC 2025

TalkRL: The Reinforcement Learning Podcast

A tartalmat a Robin Ranjit Singh Chauhan biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Robin Ranjit Singh Chauhan vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.

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We caught up with the RLC Outstanding Paper award winners for your listening pleasure.

Recorded on location at Reinforcement Learning Conference 2025, at University of Alberta, in Edmonton Alberta Canada in August 2025.

Featured References

Empirical Reinforcement Learning Research
Mitigating Suboptimality of Deterministic Policy Gradients in Complex Q-functions
Ayush Jain, Norio Kosaka, Xinhu Li, Kyung-Min Kim, Erdem Biyik, Joseph J Lim

Applications of Reinforcement Learning
WOFOSTGym: A Crop Simulator for Learning Annual and Perennial Crop Management Strategies
William Solow, Sandhya Saisubramanian, Alan Fern

Emerging Topics in Reinforcement Learning
Towards Improving Reward Design in RL: A Reward Alignment Metric for RL Practitioners
Calarina Muslimani, Kerrick Johnstonbaugh, Suyog Chandramouli, Serena Booth, W. Bradley Knox, Matthew E. Taylor

Scientific Understanding in Reinforcement Learning
Multi-Task Reinforcement Learning Enables Parameter Scaling
Reginald McLean, Evangelos Chatzaroulas, J K Terry, Isaac Woungang, Nariman Farsad, Pablo Samuel Castro

74 epizódok

#Reinforcement Learning #Machine Learning #Robin Ranjit Singh Chauhan #Artificial Intelligence #Tech