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  2. Risk and Humanities

    Duration: 01:07:29
    Published Date: 2010/02/18
    Darwin College Lecture Series 2010. "Risk and Humanities". Professor Mary Beard (Cambridge). Was there risk before modernity? This lecture explores how we might tell the ancient history of risk—from oracles (an ancient form of risk assessment) through gambling and agricultural strategies to the parade of Luck and Chance in sculptural form. In Greece and Rome (and other pre modern societies) is
  3. Slide 1

    www.tcm.phy.cam.ac.uk/~gjc29/talks/A_STAR_Talk_2020.pdf
    11 Sep 2021: Applications of random number generators. Require a random number: gambling and cryptography.
  4. 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
  5. 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: of random sequences in gambling and statistical decision. Often. one desires to know the optimal instant to bx•eak off playing a. ... Then the martingale theory o:f gambling systems or s.imply te. recurrence sN(x) = min{ x., 1[sl-f-1 (x1) N-1 (x1)] }
  6. Probability About these notes. Many people have written excellent ...

    www.statslab.cam.ac.uk/~rrw1/prob/prob-weber.pdf
    16 Sep 2019: Probability. About these notes. Many people have written excellent notes for introductorycourses in probability. Mine draw freely on material prepared by others in present-ing this course to students at Cambridge. I wish to acknowledge especially
  7. 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.
  8. 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.
  9. 22 May 2013: 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.
  10. 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.
  11. 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.

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