Arguments for the Effectiveness of Human Problem Solving

TL;DR

This paper investigates the effectiveness of human problem solving by analyzing underlying cognitive mechanisms, comparing them to an optimal probabilistic strategy, with implications for psychology and AI design.

Contribution

It introduces a framework linking human heuristics to an optimal Solomonoff-based problem solving strategy, enhancing understanding of human cognition and AI development.

Findings

Humans use heuristics similar to the Solomonoff strategy.

The effectiveness of human problem solving can be explained by specific cognitive mechanisms.

Results inform both cognitive psychology and AI agent design.

Abstract

The question of how humans solve problem has been addressed extensively. However, the direct study of the effectiveness of this process seems to be overlooked. In this paper, we address the issue of the effectiveness of human problem solving: we analyze where this effectiveness comes from and what cognitive mechanisms or heuristics are involved. Our results are based on the optimal probabilistic problem solving strategy that appeared in Solomonoff paper on general problem solving system. We provide arguments that a certain set of cognitive mechanisms or heuristics drive human problem solving in the similar manner as the optimal Solomonoff strategy. The results presented in this paper can serve both cognitive psychology in better understanding of human problem solving processes as well as artificial intelligence in designing more human-like agents.