IDEAS home Printed from https://ideas.repec.org/p/uts/rpaper/421.html
   My bibliography  Save this paper

On Approximate Solutions for Partially Observable Decision Problems

Author

Listed:
  • Juri Hinz

    (University of Technology Sydney)

Abstract

Decision problems under partial observation serve a rich framework for planning and control of operations in diverse applications. In this area, approximate point-based algorithms have emerged improving the scalability of existing numerical schemes to a key level where they can be broadly used in robotics. We elaborate on some core principles of point-based methods and present an approximate solution technique which utilizes linear state dynamics and convexity.

Suggested Citation

  • Juri Hinz, 2021. "On Approximate Solutions for Partially Observable Decision Problems," Research Paper Series 421, Quantitative Finance Research Centre, University of Technology, Sydney.
  • Handle: RePEc:uts:rpaper:421
    as

    Download full text from publisher

    File URL: https://www.uts.edu.au/sites/default/files/article/downloads/rp421.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    2. William S. Lovejoy, 1991. "Computationally Feasible Bounds for Partially Observed Markov Decision Processes," Operations Research, INFORMS, vol. 39(1), pages 162-175, February.
    3. Juri Hinz & Tanya Tarnopolskaya & Jeremy Yee, 2020. "Efficient algorithms of pathwise dynamic programming for decision optimization in mining operations," Annals of Operations Research, Springer, vol. 286(1), pages 583-615, March.
    4. Juri Hinz & Nicholas Yap, 2015. "Algorithms for Optimal Control of Stochastic Switching Systems," Research Paper Series 352, Quantitative Finance Research Centre, University of Technology, Sydney.
    5. Richard D. Smallwood & Edward J. Sondik, 1973. "The Optimal Control of Partially Observable Markov Processes over a Finite Horizon," Operations Research, INFORMS, vol. 21(5), pages 1071-1088, October.
    6. Burhaneddin Sandıkçı & Lisa M. Maillart & Andrew J. Schaefer & Mark S. Roberts, 2013. "Alleviating the Patient's Price of Privacy Through a Partially Observable Waiting List," Management Science, INFORMS, vol. 59(8), pages 1836-1854, August.
    7. Brennan, Michael J & Schwartz, Eduardo S, 1985. "Evaluating Natural Resource Investments," The Journal of Business, University of Chicago Press, vol. 58(2), pages 135-157, April.
    8. George E. Monahan, 1982. "State of the Art---A Survey of Partially Observable Markov Decision Processes: Theory, Models, and Algorithms," Management Science, INFORMS, vol. 28(1), pages 1-16, January.
    9. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," University of California at Los Angeles, Anderson Graduate School of Management qt43n1k4jb, Anderson Graduate School of Management, UCLA.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Juri Hinz & Tanya Tarnopolskaya & Jeremy Yee, 2020. "Efficient algorithms of pathwise dynamic programming for decision optimization in mining operations," Annals of Operations Research, Springer, vol. 286(1), pages 583-615, March.
    2. Sebastian Maier, 2021. "Re-evaluating natural resource investments under uncertainty: An alternative to limited traditional approaches," Annals of Operations Research, Springer, vol. 299(1), pages 907-937, April.
    3. Abdullah Almansour and Margaret Insley, 2016. "The Impact of Stochastic Extraction Cost on the Value of an Exhaustible Resource: An Application to the Alberta Oil Sands," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    4. Augusto Castillo, 2004. "Firm and Corporate Bond Valuation: A Simulation Dynamic Programming Approach," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 41(124), pages 345-360.
    5. Seiji Harikae & James S. Dyer & Tianyang Wang, 2021. "Valuing Real Options in the Volatile Real World," Production and Operations Management, Production and Operations Management Society, vol. 30(1), pages 171-189, January.
    6. Schwartz, Eduardo S., 2002. "Patents and R& D as Real Options," University of California at Los Angeles, Anderson Graduate School of Management qt86b1n43k, Anderson Graduate School of Management, UCLA.
    7. Luis M. Abadie & José M. Chamorro, 2009. "Monte Carlo valuation of natural gas investments," Review of Financial Economics, John Wiley & Sons, vol. 18(1), pages 10-22, January.
    8. David Laughton & Raul Guerrero & Donald Lessard, 2008. "Real Asset Valuation: A Back‐to‐basics Approach," Journal of Applied Corporate Finance, Morgan Stanley, vol. 20(2), pages 46-65, March.
    9. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    10. Haehl, Christian & Spinler, Stefan, 2018. "Capacity expansion under regulatory uncertainty:A real options-based study in international container shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 113(C), pages 75-93.
    11. Max F. Schöne & Stefan Spinler, 2017. "A four-factor stochastic volatility model of commodity prices," Review of Derivatives Research, Springer, vol. 20(2), pages 135-165, July.
    12. 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.
    13. Hsu, Jason C. & Schwartz, Eduardo S., 2008. "A model of R&D valuation and the design of research incentives," Insurance: Mathematics and Economics, Elsevier, vol. 43(3), pages 350-367, December.
    14. Hao Zhang, 2010. "Partially Observable Markov Decision Processes: A Geometric Technique and Analysis," Operations Research, INFORMS, vol. 58(1), pages 214-228, February.
    15. Garcia Fronti, Javier, 2015. "Modelo estocástico para la valuación de una inversión nanomédica [Nanomedical Stochastic Investment Valuation]," MPRA Paper 63948, University Library of Munich, Germany.
    16. Williams, Byron K., 2011. "Resolving structural uncertainty in natural resources management using POMDP approaches," Ecological Modelling, Elsevier, vol. 222(5), pages 1092-1102.
    17. Chung-Gee Lin & Yu-Shan Wang, 2012. "Evaluating natural resource projects with embedded options and limited reserves," Applied Economics, Taylor & Francis Journals, vol. 44(12), pages 1471-1482, April.
    18. Jain, Shashi & Roelofs, Ferry & Oosterlee, Cornelis W., 2013. "Valuing modular nuclear power plants in finite time decision horizon," Energy Economics, Elsevier, vol. 36(C), pages 625-636.
    19. Detemple, Jerome & Kitapbayev, Yerkin, 2022. "Optimal technology adoption for power generation," Energy Economics, Elsevier, vol. 111(C).
    20. Armstrong, Margaret & Langrené, Nicolas & Petter, Renato & Chen, Wen & Petter, Carlos, 2019. "Accounting for tailings dam failures in the valuation of mining projects," Resources Policy, Elsevier, vol. 63(C), pages 1-1.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:uts:rpaper:421. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Duncan Ford (email available below). General contact details of provider: https://edirc.repec.org/data/qfutsau.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.