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Title: Hybrid Model Reveals People Act Less Rationally In Complex Games, More
Predictably In Simple Ones

Link: https://science.slashdot.org/story/25/07/08/2...

alternative_right shares a report from Phys.org: Researchers at Princeton
University, Boston University and other institutes used machine learning to
predict the strategic decisions of humans in various games. Their paper,
published in Nature Human Behavior, shows that a deep neural network trained
on human decisions could predict the strategic choices of players with high
levels of accuracy. [...] Essentially, the team suggests that people behave
more rationally while playing games that they perceive as easier. In
contrast, when they are playing more complex games, people's choices could be
influenced by various other factors, thus the "noise" affecting their
behavior would increase. As part of their future studies, the researchers
would also like to shed more light on what makes a game "complex" or "easy."
This could be achieved using the context-dependent noise parameter that they
integrated into their model as a signature of "perceived difficulty." "Our
analysis provides a robust model comparison across a wide range of candidate
models of decision-making," said [Jian-Qiao Zhu, first author of the paper].
"We now have strong evidence that introducing context-dependence into the
quantal response model significantly improves its ability to capture human
strategic behavior. More specifically, we identified key factors in the game
matrix that shape game complexity: considerations of efficiency, the
arithmetic difficulty of computing payoff differences, and the depth of
reasoning required to arrive at a rational solution." The findings gathered
as part of this recent study also highlight the "lightness" with which many
people approach strategic decisions, which could make them vulnerable to
parties looking to sway them towards making irrational decisions. Once they
gather more insight into what factors make games and decision-making
scenarios more challenging for people, Zhu and his colleagues hope to start
devising new behavioral science interventions aimed at prompting people to
make more rational decisions.

Read more of this story at Slashdot.

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