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Regret Bounds for Satisficing in Multi-Armed Bandit Problems
Published in Transactions on Machine Learning Research, 2023
This paper explores the concept of satisficing in multi-armed bandit problems, where we aim to find solutions that exceed a satisfaction threshold rather than seeking optimal outcomes.
Michel, T., Hajiabolhassan, H., & Ortner, R. (2023). "Regret Bounds for Satisficing in Multi-Armed Bandit Problems." Transactions on Machine Learning Research. pdf