Robots taught to deceive

Researchers from the Georgia Institute of Technology have developed algorithms that allow a robot to determine whether it should deceive a human or other intelligent machine and which techniques to use for the best deceptive strategy. The new work, published in the International Journal of Social Robotics, is believed to be the first detailed examination of robot deception.

Georgia Tech’s Alan Wagner (right) says that robots capable of deception will likely be valuable for military and search and rescue operations. A search and rescue robot may need to deceive in order to calm or receive cooperation from a panicking victim. Robots on the battlefield with the power of deception will be able to successfully hide and mislead the enemy to keep themselves and valuable information safe.

Wagner and his co-researchers focused on the actions, beliefs and communications of a robot attempting to hide from another robot to develop programs that successfully produced deceptive behavior. Their first step was to teach the deceiving robot how to recognize a situation that warranted the use of deception. The researchers used interdependence theory and game theory to develop algorithms that tested the value of deception in a specific situation. A situation had to satisfy two key conditions to warrant deception — there must be conflict between the deceiving robot and the seeker, and the deceiver must benefit from the deception.

Once a situation was deemed to warrant deception, the robot carried out a deceptive act by providing a false communication to benefit itself. The technique developed by the Georgia Tech researchers based a robot’s deceptive action selection on its understanding of the individual robot it was attempting to deceive.

To test their algorithms, the researchers ran 20 hide-and-seek experiments with two autonomous robots. Colored markers were lined up along three potential pathways to locations where the robot could hide. The hider robot randomly selected a hiding location from the three location choices and moved toward that location, knocking down colored markers along the way. Once it reached a point past the markers, the robot changed course and hid in one of the other two locations. The presence or absence of standing markers indicated the hider’s location to the seeker robot.

“The hider’s set of false communications was defined by selecting a pattern of knocked over markers that indicated a false hiding position in an attempt to say, for example, that it was going to the right and then actually go to the left,” explained Wagner.

The hider robots were able to deceive the seeker robots in 75 percent of the trials, with the failed experiments resulting from the hiding robot’s inability to knock over the correct markers to produce the desired deceptive communication.

“The experimental results weren’t perfect, but they demonstrated the learning and use of deception signals by real robots in a noisy environment,” said Wagner. “The results were also a preliminary indication that the techniques and algorithms described in the paper could be used to successfully produce deceptive behavior in a robot.”

The researchers are not unaware of the ethical issues that robotic deception creates. “We have been concerned from the very beginning with the ethical implications related to the creation of robots capable of deception and we understand that there are beneficial and deleterious aspects,” explained co-researcher Ronald Arkin. “We strongly encourage discussion about the appropriateness of deceptive robots to determine what, if any, regulations or guidelines should constrain the development of these systems.”

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Source: Georgia Institute of Technology Research News

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