{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/from-theory-to-practice-with-raven-ucb","title":"From Theory to Practice with RAVEN-UCB: Addressing Non-Stationarity in Multi-Armed Bandits through Variance Adaptation","arxiv_id":"2506.02933","date":"2025-06-03","proceeding":null,"authors":["Junyi Fang","Yuxun Chen","Yuxin Chen","Chen Zhang"],"abstract":"The Multi-Armed Bandit (MAB) problem is challenging in non-stationary environments where reward distributions evolve dynamically. We introduce RAVEN-UCB, a novel algorithm that combines theoretical rigor with practical efficiency via variance-aware adaptation. It achieves tighter regret bounds than UCB1 and UCB-V, with gap-dependent regret of order $K \\sigma_{\\max}^2 \\log T / \\Delta$ and gap-independent regret of order $\\sqrt{K T \\log T}$. RAVEN-UCB incorporates three innovations: (1) variance-driven exploration using $\\sqrt{\\hat{\\sigma}_k^2 / (N_k + 1)}$ in confidence bounds, (2) adaptive control via $\\alpha_t = \\alpha_0 / \\log(t + \\epsilon)$, and (3) constant-time recursive updates for efficiency. Experiments across non-stationary patterns - distributional changes, periodic shifts, and temporary fluctuations - in synthetic and logistics scenarios demonstrate its superiority over state-of-the-art baselines, confirming theoretical and practical robustness.","url_abs":"https://arxiv.org/abs/2506.02933v1","url_pdf":"https://arxiv.org/pdf/2506.02933v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"from-theory-to-practice-with-raven-ucb","repo_url":"https://github.com/66661654/Raven-UCB","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"multi-armed-bandits","task_name":"Multi-Armed Bandits"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}