arxiv
PublishedMay 7, 2026 at 4:00 AM
A Harmonic Mean Formulation of Average Reward Reinforcement Learning in SMDPs
Publisher summary· verbatim
arXiv:2605.04880v1 Announce Type: new Abstract: Recent research has revived and amplified interest in algorithms for undiscounted average reward reinforcement learning in infinite-horizon, non-episodic (continuing) tasks. Semi-Markov decision processes (SMDPs) are of particular interest. In SMDPs, d
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivAn AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response9harxivLearning Transferable Latent User Preferences for Human-Aligned Decision Making9harxivRepair the Core, Not the Symptom: Planning-Graph Repair for Long-Horizon Agents9harxivIndustryForge-27B: A Domain-Enhanced Multimodal Foundation Model for Industrial CAD9hThe Bubble Brief
MON · WED · FRIRead AI insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗