Difference between revisions of "Hunting"
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==Context== | ==Context== | ||
| − | [[Bayesian Identity Proofing]] provides the means for a | + | 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 [[Attribute]]s and [[Identifier]]s as a series of authentication and verification steps to be validated. |
==Problems== | ==Problems== | ||
Revision as of 14:15, 17 August 2018
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.
Problems
Ensuring that any solution remains optimal by continually Hunting for better ones near the current one.
Solutions
- 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.
