2011 COLT COLT 2011

Monotone multi-armed bandit allocations

Abstract

We present a novel angle for multi-armed bandits (henceforth abbreviated MAB) which follows from the recent work on MAB mechanisms (Babaioff et al., 2009; Devanur and Kakade, 2009; Babaioff et al., 2010). The new problem is, essentially, about designing MAB algorithms under an additional constraint motivated by their application to MAB mechanisms. This note is self-contained, although some familiarity with MAB is assumed; we refer the reader to Cesa-Bianchi and Lugosi (2006) for more background.

🚀 Conference Pioneer — COLT 2011
🌱 Topic Pioneer — Multi-Armed Bandits
🌉 Interdisciplinary Bridge — Machine Learning and Mathematics & Optimization
📈 Trend Setter — Reinforcement Learning
🧭 Keyword Pioneer — incentive compatibility
🐣 Hot Topic Early Bird — multi-armed bandit
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Data Science & Analytics, Deep Learning, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning