Chess grandmasters are often seen as experts at thinking far ahead. But can others, with some practice, also become better at planning ahead? To answer this question, a team of cognitive scientists created a model that shows our ability to plan for future events. The study helps us understand the factors that affect decision-making and demonstrates how we can improve our planning skills through practice.
The research was conducted by scientists in New York University’s Center for Neural Science and reported in the journal Nature. It focuses on the role of “planning depth” in decision-making, which is the number of steps an individual considers ahead.
Wei Ji Ma, a professor of neuroscience and psychology at NYU, explained:
“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. Our work adds to this body of knowledge by showing that even a relatively modest amount of practice can improve depth of planning.”
Human intelligence is commonly associated with the ability to plan for the future. It is unclear, however, if skilled decision-makers plan more steps ahead than novices. The methods used to measure this ability, such as board game experiments, are often unreliable in estimating planning depth.
In the study published in Nature, participants played a game that was similar to tic-tac-toe but required players to plan ahead multiple steps. To better understand the decision-making process, the authors developed a computer model based on principles of artificial intelligence that allowed them to predict the moves made by players 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.”
The researchers found that human behavior can be represented by a computational cognitive model that uses a heuristic search algorithm. This model maps out a sequence of promising moves for both players. To prove the model’s effectiveness, the researchers conducted behavioral experiments with human participants. They monitored how players planned their moves under different scenarios, as well as tested their memory and ability to learn from their game-playing experiences. The team also conducted a Turing test experiment, where observers who had played the game before were asked to determine whether the moves they saw were made by the model or by human players. However, the observers were only able to correctly distinguish about half the time. This suggests that the model makes decisions similar to those of a human.
The study found that better planning is linked to the ability to recognize patterns more accurately and quickly. This suggests that practicing and gaining experience can be beneficial.
“It is known that cognitive abilities can improve in adulthood through practice. 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.”