W. Lovejoy's 1991 paper, “A Survey of Algorithmic Methods for Partially Observed Markov Decision Processes,” published in the Annals of Operations Research, offers an extensive review of the algorithmic techniques available for addressing partially observed Markov decision processes (POMDPs). The paper systematically categorizes and evaluates various methods, highlighting their strengths, limitations, and areas of applicability. Lovejoy discusses both exact and approximate algorithms, providing insights into their theoretical underpinnings and practical implementations. This survey has significantly contributed to the field by enhancing the understanding of POMDPs and guiding researchers and practitioners in selecting appropriate methods for decision-making problems under uncertainty. Lovejoy's work remains a cornerstone reference for those studying and applying POMDPs in various domains.