11 min listen
Detecting Cheating in Chess
FromData Skeptic
ratings:
Length:
45 minutes
Released:
May 22, 2015
Format:
Podcast episode
Description
With the advent of algorithms capable of beating highly ranked chess players, the temptation to cheat has emmerged as a potential threat to the integrity of this ancient and complex game. Yet, there are aspects of computer play that are measurably different than human play. Dr. Kenneth Regan has developed a methodology for looking at a long series of modes and measuring the likelihood that the moves may have been selected by an algorithm.
The full transcript of this episode is well annotated and has a wealth of excellent links to the things discussed.
If you're interested in learning more about Dr. Regan, his homepage (Kenneth Regan), his page on wikispaces, and the amazon page of books by Kenneth W. Regan are all great resources.
The full transcript of this episode is well annotated and has a wealth of excellent links to the things discussed.
If you're interested in learning more about Dr. Regan, his homepage (Kenneth Regan), his page on wikispaces, and the amazon page of books by Kenneth W. Regan are all great resources.
Released:
May 22, 2015
Format:
Podcast episode
Titles in the series (100)
[MINI] Bayesian Updating: In this minisode, we discuss Bayesian Updating - the process by which one can calculate the most likely hypothesis might be true given one's older / prior belief and all new evidence. by Data Skeptic