Problem valuation network

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Problem valuation network is any neural subsystem capable of estimating the value of problems to solve. Problems that maximize the reward of the solution are most likely to be tackled first (given no extrinsic valuation). Problem valuation network is based on the same priciples as knowledge valuation network and can be best visualized as a decision tree.

In education, it is important to remember that the outcome of the valuation is consistent with the Goldilocks principle. Poor understanding of this concept by teachers leads to frequent violations of the Fundamental law of learning. If your teacher believes that "children always look for easy ways", she is more likely to employ coercion in learning. Coercion often leads to learning in regress zone.

For details see: How to solve any problem?

This glossary entry is used to explain "I would never send my kids to school" (2017-2024) by Piotr Wozniak

Problem valuation optimum for problem difficulty
Problem valuation optimum for problem difficulty

Figure: Goldilocks effect in problem valuation: Harder problems are more rewarding, but are less likely to be solved. This determines optimum difficulty we look for. The expected reward will then be evaluated in the light of execution costs. Proficient problem solvers are good at spotting problems that maximize the reward. Children are quickly bored with easy games. They also give up games that go beyond their level. They naturally oscillate around games that provide maximum reward, which comes somewhere in the middle of the difficulty range. The same mechanisms work for children, adults or problem solving animals