Skip to main content

Part of the book series: Stochastic Modelling and Applied Probability ((SMAP,volume 24))

Abstract

In this chapter we define many of the standard control problems whose numerical solutions will concern us in the subsequent chapters. Other, less familiar control problems will be discussed separately in later chapters. We will first define cost functional for uncontrolled processes, and then formally discuss the partial differential equations which they satisfy. Then the cost functional for the controlled problems will be stated and the partial differential equations for the optimal cost formally derived. These partial differential equations are generally known as Bellman equations or dynamic programming equations. The main tool in the derivations is Ito’s formula.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 139.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer Science+Business Media New York

About this chapter

Cite this chapter

Kushner, H.J., Dupuis, P. (2001). Dynamic Programming Equations. In: Numerical Methods for Stochastic Control Problems in Continuous Time. Stochastic Modelling and Applied Probability, vol 24. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-0007-6_4

Download citation

  • DOI: https://doi.org/10.1007/978-1-4613-0007-6_4

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-6531-3

  • Online ISBN: 978-1-4613-0007-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics