Hunting - Revision history

Tom: /* Solutions */

2025-04-14T00:27:37Z

‎Solutions

2019-05-29T20:27:08Z

‎Solutions

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2019-05-29T20:22:43Z

‎Solutions

2019-05-29T20:21:55Z

‎Solutions

2019-05-29T20:20:50Z

‎References

2019-05-29T20:20:02Z

‎Problems

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‎Solutions

2018-08-17T22:57:39Z

‎Solutions

2018-08-17T21:32:22Z

‎Solutions

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 *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, [[Conservative Systems]] 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]].

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 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. It is very likely to find local maximum values and never look far from that maximum.
-*A liberal [[Hunting]] algorithm will seek further afield for better solutions. In learning this means that some measure of randomness needs to be introduced.<ref>Geoffrey Hinton quoted in Neil Savage, ''Neural Net Worth.'' '''CACM Vol 62''' no 6 p. 12 (2019-06)</ref>
+*A liberal [[Hunting]] algorithm will seek further afield for better solutions. In learning this means that some measure of randomness needs to be introduced.<ref name=hinton>Geoffrey Hinton quoted in Neil Savage, ''Neural Net Worth.'' '''CACM Vol 62''' no 6 p. 12 (2019-06)</ref>
 *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]].

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 ==Problems==
-Ensuring that any solution remains optimal by continually [[Hunting]] for better ones only near the current one is likely to trapped in a sub-optimal local maximum value that could be improved by looking further in the range space of possible solutions.
+* Ensuring that any solution remains optimal by continually [[Hunting]] for better ones only near the current one is likely to trapped in a sub-optimal local maximum value that could be improved by looking further in the range space of possible solutions.
 ==Solutions==

@@ Line 11: / Line 11: @@
 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. It is very likely to find local maximum values and never look far from that maximum.
-*A liberal [[Hunting]] algorithm will seek further afield for better solutions. In learning this means that some measure of randomness needs to be introduced.<ref>Geoffrey Hinton quoted in Neil Savage, ''Neural Net Worth.'' CACM Vol 62 no 6 p. 12 (2019-06)</ref>
+*A liberal [[Hunting]] algorithm will seek further afield for better solutions. In learning this means that some measure of randomness needs to be introduced.<ref>Geoffrey Hinton quoted in Neil Savage, ''Neural Net Worth.'' '''CACM Vol 62''' no 6 p. 12 (2019-06)</ref>
 *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]].

@@ Line 11: / Line 11: @@
 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. It is very likely to find local maximum values and never look far from that maximum.
-*A liberal [[Hunting]] algorithm will seek further afield for better solutions. In learning this means that some measure of randomness needs to be introduced.<ref>Geoffrey Hinton quoted in Neil Savage, ''Neural Net Worth.'' CACM Vol 62 no6 p. 12</ref>
+*A liberal [[Hunting]] algorithm will seek further afield for better solutions. In learning this means that some measure of randomness needs to be introduced.<ref>Geoffrey Hinton quoted in Neil Savage, ''Neural Net Worth.'' CACM Vol 62 no 6 p. 12 (2019-06)</ref>
 *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]].