Can we learn to think further ahead?
Cognitive scientists' computational model shows how expertise improves planning depth

Date:
May 31, 2023
Source:
New York University
Summary:
Chess grandmasters are often held up as the epitome of thinking
far ahead. But can others, with a modest amount of practice,
learn to think further ahead? In addressing this question, a team
of cognitive scientists has created a computational model that
reveals our ability to plan for future events. The work enhances
our understanding of the factors that affect decision-making and
shows how we can boost our planning skills through practice.


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FULL STORY ========================================================================== Chess grandmasters are often held up as the epitome of thinking far
ahead. But can others, with a modest amount of practice, learn to
think further ahead? In addressing this question, a team of cognitive scientists has created a computational model that reveals our ability
to plan for future events. The work enhances our understanding of the
factors that affect decision-making and shows how we can boost our
planning skills through practice.

The research, conducted by scientists in New York University's Center for Neural Science and reported in the journal Nature, centers on the role of "planning depth" -- the number of steps that an individual thinks ahead --
in decision-making.

"While artificial intelligence has made impressive progress in solving
complex planning problems, much less is understood about the nature
and depth of planning in people," explains Wei Ji Ma, a professor of neuroscience and psychology at NYU and the paper's senior author. "Our
work adds to this body of knowledge by showing that even a relatively
modest amount of practice can improve depth of planning." It's been long established that a hallmark of human intelligence is the ability to plan multiple steps into the future. However, it's less clear whether or not
skilled decision makers plan more steps ahead than do novices. This is
because methods for measuring this aptitude (e.g., experiments involving
board games) have notable shortcomings -- in part, because they don't
reliably estimate planning depth.

The Naturepaper's authors had people play a relatively simple game --
a more sophisticated version of tic-tac-toe -- that still required
players to plan deeply (i.e., multiple steps ahead). Then, to understand precisely what goes on in people's minds as they are thinking of their
next move in this game, the authors designed a computer model based on
AI principles. The model allows them to describe and subsequently predict
the moves that people make when faced with new situations in the game.

"In this computational model, players build a 'decision tree' in their
heads the same way that you might plan for multiple possible scenarios
for a complex travel itinerary," Ma explains.

Here, their calculations showed that human behavior can be captured using
a computational cognitive model based on a heuristic search algorithm --
one that maps out a sequence of promising moves for both players.

To validate the model, the researchers conducted a series of behavioral experiments with human participants. Specifically, they tracked how
players planned their moves under different scenarios while also testing
their memory and their ability to learn from and reconstruct their
game-playing experiences.

In addition, the team conducted a Turing test experiment in which
observers, who had played the game before, were asked to determine whether sequences of moves they witnessed were generated by the model or by human players. These observers were able to make the correct distinction only
about half the time, suggesting that the model makes similar decisions
that a human would make.

Several of these experiments may be played online by going to Ma's
laboratory website.

Overall, their results showed that better planning is driven by the
ability to recognize patterns more accurately and in less time --
outcomes that point to the benefits of practice and experience.

"It is known that cognitive abilities can improve in adulthood through practice," observes Ma. "These findings show that even a relatively
modest amount of practice can improve one's depth of planning. This
opens up new avenues of research. For example, we can use these methods
to study the development of planning abilities in children, or test
whether planning abilities can be retained in old age. Of course, it is
also crucial that we connect planning in the laboratory to planning in
real life." The paper's other authors are: Bas van Opheusden, an NYU
doctoral student at the time of the study and now a research scientist at Generally Intelligent; Ionatan Kuperwajs, an NYU doctoral student; Gianni Galbiati, an NYU researcher at the time of the study and now director of research and development at Vidrovr; Zahy Bnaya, a postdoctoral researcher
at NYU's Center for Neural Science; and Yunqi Li, an NYU researcher at
the time of the study and now a doctoral student at Stanford University.

The research was supported by grants from the National Science Foundation
(IIS- 1344256, DGE1839302).

* RELATED_TOPICS
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========================================================================== Story Source: Materials provided by New_York_University. Note: Content
may be edited for style and length.


========================================================================== Journal Reference:
1. van Opheusden, B., Kuperwajs, I., Galbiati, G. et al. Expertise
increases
planning depth in human gameplay. Nature, 2023 DOI:
10.1038/s41586-023- 06124-2 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2023/05/230531150112.htm

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