Summary of Kalmamba: Towards Efficient Probabilistic State Space Models For Rl Under Uncertainty, by Philipp Becker et al.
KalMamba: Towards Efficient Probabilistic State Space Models for RL under Uncertaintyby Philipp Becker, Niklas Freymuth,…
Summary of Open Problem: Order Optimal Regret Bounds For Kernel-based Reinforcement Learning, by Sattar Vakili
Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learningby Sattar VakiliFirst submitted to arxiv…
Summary of An Idiosyncrasy Of Time-discretization in Reinforcement Learning, by Kris De Asis et al.
An Idiosyncrasy of Time-discretization in Reinforcement Learningby Kris De Asis, Richard S. SuttonFirst submitted to…
Summary of Sit: Symmetry-invariant Transformers For Generalisation in Reinforcement Learning, by Matthias Weissenbacher et al.
SiT: Symmetry-Invariant Transformers for Generalisation in Reinforcement Learningby Matthias Weissenbacher, Rishabh Agarwal, Yoshinobu KawaharaFirst submitted…
Summary of Behaviour Distillation, by Andrei Lupu et al.
Behaviour Distillationby Andrei Lupu, Chris Lu, Jarek Liesen, Robert Tjarko Lange, Jakob FoersterFirst submitted to…
Summary of Direct Multi-turn Preference Optimization For Language Agents, by Wentao Shi et al.
Direct Multi-Turn Preference Optimization for Language Agentsby Wentao Shi, Mengqi Yuan, Junkang Wu, Qifan Wang,…
Summary of A Benchmark Study Of Deep-rl Methods For Maximum Coverage Problems Over Graphs, by Zhicheng Liang et al.
A Benchmark Study of Deep-RL Methods for Maximum Coverage Problems over Graphsby Zhicheng Liang, Yu…
Summary of A General Control-theoretic Approach For Reinforcement Learning: Theory and Algorithms, by Weiqin Chen et al.
A General Control-Theoretic Approach for Reinforcement Learning: Theory and Algorithmsby Weiqin Chen, Mark S. Squillante,…
Summary of Rl on Incorrect Synthetic Data Scales the Efficiency Of Llm Math Reasoning by Eight-fold, By Amrith Setlur et al.
RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Foldby Amrith…
Summary of Macrohft: Memory Augmented Context-aware Reinforcement Learning on High Frequency Trading, by Chuqiao Zong et al.
MacroHFT: Memory Augmented Context-aware Reinforcement Learning On High Frequency Tradingby Chuqiao Zong, Chaojie Wang, Molei…