Hunting

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Full Title or Meme

A process (usually expressed as an algorithm) for seeking a better solution.

Context

The process of improving the algorithms used in Identity Management is an on-going effort to select and evaluate changes to the process used. Bayesian Identity Proofing provides the means for evaluating a Trust Vector of Attributes and Identifiers as a series of authentication and verification steps to be validated. Such algorithms are typically improved by selecting changes and then testing them to assure that both the Assurance of the data collected as well as the User Experience has improved. In other words, this is about Evolution. J. B. S. Haldane was the first to create "A Mathematical Theory of Natural and Artificial Selection"[1]. He required a determination of two variables (1) the intensity of selection and (2) The rate at which the old methods are removed from circulation. These same method can be used today in the process of tuning the Hunting algorithm to create the most rapid change possible that both increases the quality of the algorithm without destroying the viability of the Entity using the algorithm all while still thriving in the constantly changing Ecosystem.

Problems

Ensuring that any solution remains optimal by continually Hunting for better ones near the current one.

Solutions

These are some of the considerations to be used for determining (1) the rate and complexity of the changes introduced, and (2) the rate at which the older algorithms are retired. With the assumption that the Web Site testing the changes is using A/B Testing.

  • A conservative Hunting algorithm will seek only solutions near to the current one.
  • A liberal Hunting algorithm will seek further afield for better solutions.
  • As in politics, a conservative algorithm will result in less Disruption and will often get trapped by local maxima, just as a hill climbing algorithm will.
  • As in politics, a liberal solution will be needed when the conservative solutions diverge too far from the higher level goals by gradual Evolution.
  • As in politics, a conservative algorithm will eventually result in the destruction of the system by external Disruption or revolution from within.
  • As in politics, a constant (but acceptable) shifting between liberal and conservative algorithms will provide adaption of the solution without unacceptable Disruption.

References

  1. J. B. S. Haldane, A Mathematical Theory of Natural and Artificial Selection. a ten part essay, the first is published by Cambridge Philosophical Society 23 pp 19-41 (1924) https://web.archive.org/web/20041123231709/http://www.blackwellpublishing.com:80/ridley/classictexts/haldane1.pdf