Duke University researchers have developed an algorithm capable of determining the best strategy for winning a game of CLUE©, a mathematical model that also could be used to help robotic mine sweepers find hidden explosives. Duke post-doctoral fellow Chenghui Cai says robotic sensors, like players in CLUE©, take information from their surroundings to help the robot maneuver around obstacles and find its target. "The key to success, both for the CLUE© player and the robots, is to not only take in the new information it discovers, but to use this new information to help guide its next move," Cai says. "This learning-adapting process continues until either the player has won the game, or the robot has found the mines." Artificial intelligence researchers call these situations "treasure hunt" problems, and have developed mathematical approaches to improving the chances of discovering the hidden treasure. Cai says the researchers found that players who implement the strategies based on the algorithm consistently outperform human players and other computer programs. Duke professor Silvia Ferrari, director of Duke's Laboratory for Intelligent Systems and Controls, says the algorithm is designed to maximize the ability to reach targets while minimizing the amount of movement.
Duke University News & Communications (01/27/09) Merritt, Richard
