Autonomous Agent for Deception Detection

Amos Azaria, Ariella Richardson, S. Kraus

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Autonomous agents can be of assistance in detecting and reducing deception in computerized forums and chat-rooms. Although some deception detection methods exist they heavily rely on audio and visual information. Our focus is on text-based environments where there is no data of this type to use. We have developed DIG, an innovative machine learning-based autonomous agent, which joins a group of players as a regular member and assists them in catching a deceiver. We introduce “the pirate game” as a platform for deploying this agent. Our experimental study shows that although humans display difficulty detecting deception, DIG is not only capable of finding a deceptive player, but it also helps increase the entire group's success.
Original languageEnglish
Title of host publicationHAIDM (In AAMAS)
Number of pages12
StatePublished - 2013


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