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  2. Optimization and Control · Course Blog

    www.statslab.cam.ac.uk/~rrw1/oc/blog.html
    16 Mar 2012: In Section 4.3 (optimal gambling) we saw that timid play is optimal in the gambling problem when the game is favorable to the gambler (p>=0.5). ... If p=0.5 all strategies are optimal. How could we prove that?
  3. L.dvi

    www.statslab.cam.ac.uk/~rrw1/oc/L2010a4.pdf
    25 Nov 2010: 13. 4.2 Characterization of the optimal policy. 13. 4.3 Example: optimal gambling. ... Either way, we have F(π, x) F(π′, x). 13. 4.3 Example: optimal gambling.
  4. L.dvi

    www.statslab.cam.ac.uk/~rrw1/oc/La5.pdf
    14 Jun 2007: 134.2 Characterization of the optimal policy. 134.3 Example: optimal gambling. 144.4 Value iteration. ... Either way, we have F (π, x) F (π′, x). 4.3 Example: optimal gambling.
  5. DOMINANT STRATEGIES IN STOCHASTIC ALLOCATION AND SCHEDULING PROBLEMS…

    www.statslab.cam.ac.uk/~rrw1/publications/Weber%20-%20Nash%201982%20Dominant%20strategies%20in%20stochastic%20allocation%20and%20scheduling%20problems.pdf
    18 Sep 2011: The condition is used to establish the nature of the optimal strategies for problems of customer assignment, dynamic memory allocation, optimal gambling, maintenance and scheduling. ... Example 3. Optimal Gambling. Ross [8J considers a problem of
  6. Gambling for redemption or ripoff? - News & insight - Cambridge…

    https://www.jbs.cam.ac.uk/2022/gambling-for-redemption-or-ripoff/
    Gambling for ripoff, which means taking a very big risk, benefiting the owners at the expense of the creditors and overall efficiency – like an “asset substitution on steroids.” Ripoff is optimal ... be pushed into bankruptcy, and gambling is only
  7. Markov Chains Course Blog

    www.statslab.cam.ac.uk/~rrw1/markov/blog.html
    4 Sep 2012: The optimal sampling theorem also gives us a quick way to answer the first part of Example Sheet 1 #10. ... This fact is proved in the Part II course Optimization and Control (see Section 4.3 "Optimal gambling" in the Optimization and Control course notes
  8. https://www.jbs.cam.ac.uk/tag/financial-risk/feed/

    https://www.jbs.cam.ac.uk/tag/financial-risk/feed/
    28 Jun 2024: Gambling for ripoff, which means taking a very big risk, benefiting the owners at the expense of the creditors and overall efficiency – like an “asset substitution on steroids.” Ripoff is optimal ... be pushed into bankruptcy, and gambling is only
  9. Optimization and Control J.R. Norris November 22, 2007 1 ...

    www.statslab.cam.ac.uk/~james/Lectures/oc.pdf
    22 Nov 2007: X0,. , Xn). Define also the optimal reward or value function. V (x) = supu. ... Example (Optimal gambling). A gambler has one pound and wishes to increase it to Npounds.
  10. https://www.jbs.cam.ac.uk/tag/financial-markets/feed/

    https://www.jbs.cam.ac.uk/tag/financial-markets/feed/
    28 Jun 2024: Gambling for ripoff, which means taking a very big risk, benefiting the owners at the expense of the creditors and overall efficiency – like an “asset substitution on steroids.” Ripoff is optimal ... be pushed into bankruptcy, and gambling is only
  11. 30 Jun 2024: Gambling for ripoff, which means taking a very big risk, benefiting the owners at the expense of the creditors and overall efficiency – like an “asset substitution on steroids.” Ripoff is optimal ... be pushed into bankruptcy, and gambling is only
  12. 4 Dynamic optimization for non-negative rewards We show how ...

    www.statslab.cam.ac.uk/~james/Lectures/oc4.pdf
    22 Nov 2007: X0,. , Xn). Define also the optimal reward or value function. V (x) = supu. ... Example (Optimal gambling). A gambler has one pound and wishes to increase it to Npounds.
  13. THE THEORY OF OPTIMAL STOPPING RICHARD Re WEBER DOWNING ...

    www.statslab.cam.ac.uk/~rrw1/publications/The%20theory%20of%20optimal%20stopping%20(Part%20III%20essay).pdf
    21 Oct 2011: THE THEORY OF OPTIMAL STOPPING. RICHARD Re WEBER. DOWNING COLLEGE. C.Ali!BRIDGE. ... of random sequences in gambling and statistical decision. Often. one desires to know the optimal instant to bx•eak off playing a.
  14. 8 Mar 2016: 13. 4.2 Characterization of the optimal policy. 13. 4.3 Example: optimal gambling. ... Either way, we have F(π,x) F(π′,x). 13. 4.3 Example: optimal gambling.
  15. 29 Nov 2014: 13. 4.2 Characterization of the optimal policy. 13. 4.3 Example: optimal gambling. ... Either way, we have F(π,x) F(π′,x). 13. 4.3 Example: optimal gambling.
  16. 21 Mar 2012: 13. 4.2 Characterization of the optimal policy. 13. 4.3 Example: optimal gambling. ... Either way, we have F(π, x) F(π′, x). 13. 4.3 Example: optimal gambling.

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