Experimental psychologist Marcia Spetch and computer scientist Vadim Bulitko used their research to understand the reasoning and decision-making process involved in hiding and searching for objects.
They believe that it will lead to more realistic game environments, and even advanced search-enhancing tools for law enforcement.
The study focuses on a multi-phase study that involved adult participants searching for and hiding objects in a room in a virtual-reality setting resembling the real room's dimensions.
The researchers found that people who were searching for objects tended to look in places closer to their starting location, whereas people tended to move farthest away from the starting point when hiding objects.
The hiders would disperse objects over a wider area to make them harder to find.
On role-reversal, this group provided the researchers with some interesting observations.
"People that had already hidden objects tended to move further away from the starting place consistent with where people normally hide objects. It was as though the hiding primed them into what kinds of locations things might be hidden in," said Spetch.
Understanding peoples' hiding behaviours and considering their motivations and other factors (time, stress, value of an object) would help researchers in mapping out and predicting ideal hiding spots in any given space.
Gamers would benefit directly from this knowledge, as it will allow programmers to hide objects in more interesting locations within a game, based on peoples' real-life search strategies.
The information will give programmers more information they can use to make computer-generated characters, or game-bots, more human-like by giving them human characteristics and limitations.
Bulitko said that this makes the game more fun for the players.
He is hoping for a law enforcement application using computer-enhanced eyewear similar to technology currently available in military circles.
By analysing a room, the search-enhancing goggles could help limit the number of possible spots where an object may be hidden.
"A computer can recognize spots in a room, and maybe it can make some suggestions like 'OK, check under that plank on the floor,'" he said.
The study has been published in Learning and Motivation.