Cognitive Scaffold

Preparing your thinking workspace

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MENTAL MODEL · M1752

Local Maximum

Local Maximum
TechnicalHigh supportAlgorithms
Included
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Version 1.0.0 · Updated 2026-07-30

CORE DEFINITION

In hill-climbing algorithms, you climb to a peak, all around is downhill, you think you've reached the highest point (global maximum), but there is actually a higher mountain nearby (global maximum), but to get there you must first go downhill (temporarily worse).

SCAFFOLDING EFFECT

psychology

Reduce cognitive load

- Transformation courage: When you can't improve performance even with more effort, you may be stuck at a local maximum. You must dare to accept short-term performance decline (downhill) to switch tracks (find a higher mountain), otherwise you can only engage in low-level involution.

anchor

Anchor fast decisions

In hill-climbing algorithms, reaching a peak (local maximum) makes you think you've reached the top, all around is downhill, but you need to go downhill first to reach a higher mountain (global maximum). The mechanism is that the 'instinct for improvement' locks you into a suboptimal point.

MINIMUM ACTION

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Source support: Explicit

  • link
    en.wikipedia.orghttps://en.wikipedia.org/wiki/Maximum_and_minimumZH · Explicit
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