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State of the Art---A Survey of Partially Observable Markov Decision Processes: Theory, Models, and Algorithms

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  1. Turgay Ayer & Oguzhan Alagoz & Natasha K. Stout, 2012. "OR Forum---A POMDP Approach to Personalize Mammography Screening Decisions," Operations Research, INFORMS, vol. 60(5), pages 1019-1034, October.
  2. Abhijit Gosavi, 2009. "Reinforcement Learning: A Tutorial Survey and Recent Advances," INFORMS Journal on Computing, INFORMS, vol. 21(2), pages 178-192, May.
  3. Özgür-Ünlüakın, Demet & Bilgiç, Taner, 2017. "Performance analysis of an aggregation and disaggregation solution procedure to obtain a maintenance plan for a partially observable multi-component system," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 652-662.
  4. Ricardo Montoya & Oded Netzer & Kamel Jedidi, 2010. "Dynamic Allocation of Pharmaceutical Detailing and Sampling for Long-Term Profitability," Marketing Science, INFORMS, vol. 29(5), pages 909-924, 09-10.
  5. James T. Treharne & Charles R. Sox, 2002. "Adaptive Inventory Control for Nonstationary Demand and Partial Information," Management Science, INFORMS, vol. 48(5), pages 607-624, May.
  6. Yanling Chang & Alan Erera & Chelsea White, 2015. "Value of information for a leader–follower partially observed Markov game," Annals of Operations Research, Springer, vol. 235(1), pages 129-153, December.
  7. Abraham Grosfeld‐Nir & Eyal Cohen & Yigal Gerchak, 2007. "Production to order and off‐line inspection when the production process is partially observable," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(8), pages 845-858, December.
  8. Boloori, Alireza & Saghafian, Soroush & Chakkera, Harini A. A. & Cook, Curtiss B., 2017. "Data-Driven Management of Post-transplant Medications: An APOMDP Approach," Working Paper Series rwp17-036, Harvard University, John F. Kennedy School of Government.
  9. Baggio, Michele & Fackler, Paul L., 2016. "Optimal management with reversible regime shifts," Journal of Economic Behavior & Organization, Elsevier, vol. 132(PB), pages 124-136.
  10. Xiaoli Fan & Miguel I. Gómez & Shady S. Atallah & Jon M. Conrad, 2020. "A Bayesian State‐Space Approach for Invasive Species Management: The Case of Spotted Wing Drosophila," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1227-1244, August.
  11. İ. Esra Büyüktahtakın & Robert G. Haight, 2018. "A review of operations research models in invasive species management: state of the art, challenges, and future directions," Annals of Operations Research, Springer, vol. 271(2), pages 357-403, December.
  12. Faddoul, R. & Raphael, W. & Chateauneuf, A., 2018. "Maintenance optimization of series systems subject to reliability constraints," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 179-188.
  13. Gong, Linguo & Tang, Kwei, 1997. "Monitoring machine operations using on-line sensors," European Journal of Operational Research, Elsevier, vol. 96(3), pages 479-492, February.
  14. Givon, Moshe & Grosfeld-Nir, Abraham, 2008. "Using partially observed Markov processes to select optimal termination time of TV shows," Omega, Elsevier, vol. 36(3), pages 477-485, June.
  15. Y-H Kim & L C Thomas, 2006. "Repair strategies in an uncertain environment: Markov decision process approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(8), pages 957-964, August.
  16. Yossi Aviv & Amit Pazgal, 2005. "A Partially Observed Markov Decision Process for Dynamic Pricing," Management Science, INFORMS, vol. 51(9), pages 1400-1416, September.
  17. Andrew J. Keith & Darryl K. Ahner, 2021. "A survey of decision making and optimization under uncertainty," Annals of Operations Research, Springer, vol. 300(2), pages 319-353, May.
  18. Lian, Zhaotong & Deshmukh, Abhijit, 2006. "Performance prediction of an unmanned airborne vehicle multi-agent system," European Journal of Operational Research, Elsevier, vol. 172(2), pages 680-695, July.
  19. Arifoglu, Kenan & Özekici, Süleyman, 2010. "Optimal policies for inventory systems with finite capacity and partially observed Markov-modulated demand and supply processes," European Journal of Operational Research, Elsevier, vol. 204(3), pages 421-438, August.
  20. Kıvanç, İpek & Özgür-Ünlüakın, Demet & Bilgiç, Taner, 2022. "Maintenance policy analysis of the regenerative air heater system using factored POMDPs," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
  21. Fackler, Paul L. & Haight, Robert G., 2014. "Monitoring as a partially observable decision problem," Resource and Energy Economics, Elsevier, vol. 37(C), pages 226-241.
  22. Pirayesh Neghab, Davood & Khayyati, Siamak & Karaesmen, Fikri, 2022. "An integrated data-driven method using deep learning for a newsvendor problem with unobservable features," European Journal of Operational Research, Elsevier, vol. 302(2), pages 482-496.
  23. Xin Jin, 2021. "Can we imitate the principal investor's behavior to learn option price?," Papers 2105.11376, arXiv.org, revised Jan 2022.
  24. White, Benedict, 2002. "Optimal Monitoring of Agri-environmental Schemes," 2002 Conference (46th), February 13-15, 2002, Canberra, Australia 125606, Australian Agricultural and Resource Economics Society.
  25. Arnoud V. den Boer & Bert Zwart, 2015. "Dynamic Pricing and Learning with Finite Inventories," Operations Research, INFORMS, vol. 63(4), pages 965-978, August.
  26. T Sloan, 2010. "First, do no harm? A framework for evaluating new versus reprocessed medical devices," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(2), pages 191-201, February.
  27. Wooseung Jang & J. George Shanthikumar, 2002. "Stochastic allocation of inspection capacity to competitive processes," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(1), pages 78-94, February.
  28. V. Makis & X. Jiang, 2003. "Optimal Replacement Under Partial Observations," Mathematics of Operations Research, INFORMS, vol. 28(2), pages 382-394, May.
  29. Paul L Fackler & Krishna Pacifici & Julien Martin & Carol McIntyre, 2014. "Efficient Use of Information in Adaptive Management with an Application to Managing Recreation near Golden Eagle Nesting Sites," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-14, August.
  30. Alireza Boloori & Soroush Saghafian & Harini A. Chakkera & Curtiss B. Cook, 2020. "Data-Driven Management of Post-transplant Medications: An Ambiguous Partially Observable Markov Decision Process Approach," Manufacturing & Service Operations Management, INFORMS, vol. 22(5), pages 1066-1087, September.
  31. Hao Zhang, 2010. "Partially Observable Markov Decision Processes: A Geometric Technique and Analysis," Operations Research, INFORMS, vol. 58(1), pages 214-228, February.
  32. Carolina Saavedra Sueldo & Ivo Perez Colo & Mariano De Paula & Sebastián A. Villar & Gerardo G. Acosta, 2023. "ROS-based architecture for fast digital twin development of smart manufacturing robotized systems," Annals of Operations Research, Springer, vol. 322(1), pages 75-99, March.
  33. Anyan Qi & Hyun-Soo Ahn & Amitabh Sinha, 2017. "Capacity Investment with Demand Learning," Operations Research, INFORMS, vol. 65(1), pages 145-164, February.
  34. Chiel van Oosterom & Lisa M. Maillart & Jeffrey P. Kharoufeh, 2017. "Optimal maintenance policies for a safety‐critical system and its deteriorating sensor," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(5), pages 399-417, August.
  35. Zhang, Ling & Zhang, Hao & Yao, Haixiang, 2018. "Optimal investment management for a defined contribution pension fund under imperfect information," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 210-224.
  36. Armando Z. Milioni & Stanley R. Pliska, 1988. "Optimal inspection under semi‐markovian deterioration: Basic results," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(5), pages 373-392, October.
  37. Otten, Maarten & Timmer, Judith & Witteveen, Annemieke, 2020. "Stratified breast cancer follow-up using a continuous state partially observable Markov decision process," European Journal of Operational Research, Elsevier, vol. 281(2), pages 464-474.
  38. Serin, Yasemin, 1995. "A nonlinear programming model for partially observable Markov decision processes: Finite horizon case," European Journal of Operational Research, Elsevier, vol. 86(3), pages 549-564, November.
  39. Jue Wang, 2016. "Minimizing the false alarm rate in systems with transient abnormality," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(4), pages 320-334, June.
  40. Jingyu Zhang & Brian T. Denton & Hari Balasubramanian & Nilay D. Shah & Brant A. Inman, 2012. "Optimization of Prostate Biopsy Referral Decisions," Manufacturing & Service Operations Management, INFORMS, vol. 14(4), pages 529-547, October.
  41. Ali Hajjar & Oguzhan Alagoz, 2023. "Personalized Disease Screening Decisions Considering a Chronic Condition," Management Science, INFORMS, vol. 69(1), pages 260-282, January.
  42. Haight, Robert G. & Polasky, Stephen, 2010. "Optimal control of an invasive species with imperfect information about the level of infestation," Resource and Energy Economics, Elsevier, vol. 32(4), pages 519-533, November.
  43. Juri Hinz, 2021. "On Approximate Solutions for Partially Observable Decision Problems," Research Paper Series 421, Quantitative Finance Research Centre, University of Technology, Sydney.
  44. Dinah Rosenberg & Eilon Solan & Nicolas Vieille, 2009. "Protocols with No Acknowledgment," Operations Research, INFORMS, vol. 57(4), pages 905-915, August.
  45. Wolfram Wiesemann & Daniel Kuhn & Berç Rustem, 2013. "Robust Markov Decision Processes," Mathematics of Operations Research, INFORMS, vol. 38(1), pages 153-183, February.
  46. Arifoglu, Kenan & Özekici, Süleyman, 2011. "Inventory management with random supply and imperfect information: A hidden Markov model," International Journal of Production Economics, Elsevier, vol. 134(1), pages 123-137, November.
  47. Malek Ebadi & Raha Akhavan-Tabatabaei, 2021. "Personalized Cotesting Policies for Cervical Cancer Screening: A POMDP Approach," Mathematics, MDPI, vol. 9(6), pages 1-20, March.
  48. Rafic Faddoul & Abdul-Hamid Soubra & Wassim Raphael & Alaa Chateauneuf, 2013. "Extension of dynamic programming models for management optimization from single structure to multi-structures level," Post-Print hal-01006860, HAL.
  49. Fawad Naseer & Muhammad Nasir Khan & Ali Altalbe, 2023. "Telepresence Robot with DRL Assisted Delay Compensation in IoT-Enabled Sustainable Healthcare Environment," Sustainability, MDPI, vol. 15(4), pages 1-15, February.
  50. Stephen M. Gilbert & Hena M Bar, 1999. "The value of observing the condition of a deteriorating machine," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(7), pages 790-808, October.
  51. Tianhu Deng & Zuo-Jun Max Shen & J. George Shanthikumar, 2014. "Statistical Learning of Service-Dependent Demand in a Multiperiod Newsvendor Setting," Operations Research, INFORMS, vol. 62(5), pages 1064-1076, October.
  52. Zong-Zhi Lin & James C. Bean & Chelsea C. White, 2004. "A Hybrid Genetic/Optimization Algorithm for Finite-Horizon, Partially Observed Markov Decision Processes," INFORMS Journal on Computing, INFORMS, vol. 16(1), pages 27-38, February.
  53. Abderrahmane Abbou & Viliam Makis, 2019. "Group Maintenance: A Restless Bandits Approach," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 719-731, October.
  54. Lu Jin & Undarmaa Bayarsaikhan & Kazuyuki Suzuki, 2016. "Optimal control limit policy for age-dependent deteriorating systems under incomplete observations," Journal of Risk and Reliability, , vol. 230(1), pages 34-43, February.
  55. Kazmi, Hussain & Suykens, Johan & Balint, Attila & Driesen, Johan, 2019. "Multi-agent reinforcement learning for modeling and control of thermostatically controlled loads," Applied Energy, Elsevier, vol. 238(C), pages 1022-1035.
  56. Ciriaco Valdez‐Flores & Richard M. Feldman, 1989. "A survey of preventive maintenance models for stochastically deteriorating single‐unit systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 36(4), pages 419-446, August.
  57. Churlzu Lim & J. Neil Bearden & J. Cole Smith, 2006. "Sequential Search with Multiattribute Options," Decision Analysis, INFORMS, vol. 3(1), pages 3-15, March.
  58. Saghafian, Soroush, 2018. "Ambiguous partially observable Markov decision processes: Structural results and applications," Journal of Economic Theory, Elsevier, vol. 178(C), pages 1-35.
  59. Kobayashi, Teruyoshi, 2009. "Announcements and the effectiveness of monetary policy: A view from the US prime rate," Journal of Banking & Finance, Elsevier, vol. 33(12), pages 2253-2266, December.
  60. Shoshana Anily & Abraham Grosfeld-Nir, 2006. "An Optimal Lot-Sizing and Offline Inspection Policy in the Case of Nonrigid Demand," Operations Research, INFORMS, vol. 54(2), pages 311-323, April.
  61. Anyan Qi & Hyun-Soo Ahn & Amitabh Sinha, 2017. "Capacity Investment with Demand Learning," Operations Research, INFORMS, vol. 65(1), pages 145-164, February.
  62. Papakonstantinou, K.G. & Shinozuka, M., 2014. "Planning structural inspection and maintenance policies via dynamic programming and Markov processes. Part I: Theory," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 202-213.
  63. Vishal Ahuja & John R. Birge, 2020. "An Approximation Approach for Response-Adaptive Clinical Trial Design," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 877-894, October.
  64. Williams, Byron K., 2009. "Markov decision processes in natural resources management: Observability and uncertainty," Ecological Modelling, Elsevier, vol. 220(6), pages 830-840.
  65. Jue Wang & Chi-Guhn Lee, 2015. "Multistate Bayesian Control Chart Over a Finite Horizon," Operations Research, INFORMS, vol. 63(4), pages 949-964, August.
  66. Grosfeld-Nir, Abraham, 2007. "Control limits for two-state partially observable Markov decision processes," European Journal of Operational Research, Elsevier, vol. 182(1), pages 300-304, October.
  67. Chernonog, Tatyana & Avinadav, Tal, 2016. "A two-state partially observable Markov decision process with three actionsAuthor-Name: Ben-Zvi, Tal," European Journal of Operational Research, Elsevier, vol. 254(3), pages 957-967.
  68. Yeek-Hyun Kim & Lyn Thomas, 2013. "Training and repair policies for stand-by systems," Annals of Operations Research, Springer, vol. 208(1), pages 469-487, September.
  69. Jang, Wooseung & Shanthikumar, J. George, 2004. "Sequential process control under capacity constraints," European Journal of Operational Research, Elsevier, vol. 155(3), pages 695-714, June.
  70. Turgay Ayer & Oguzhan Alagoz & Natasha K. Stout & Elizabeth S. Burnside, 2016. "Heterogeneity in Women’s Adherence and Its Role in Optimal Breast Cancer Screening Policies," Management Science, INFORMS, vol. 62(5), pages 1339-1362, May.
  71. Williams, Byron K., 2011. "Resolving structural uncertainty in natural resources management using POMDP approaches," Ecological Modelling, Elsevier, vol. 222(5), pages 1092-1102.
  72. Yanling Chang & Alan Erera & Chelsea White, 2015. "A leader–follower partially observed, multiobjective Markov game," Annals of Operations Research, Springer, vol. 235(1), pages 103-128, December.
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