Machines Learn To Cooperate With Human Partners, Who Often Cheat or Become Disloyal

MedicalResearch.com Interview with:

Jacob Crandall PhD Associate Professsor, Computer Science Brigham Young University 

Dr. Jacob Crandall

Jacob Crandall PhD
Associate Professsor, Computer Science
Brigham Young University 

MedicalResearch.com: What is the background for this study?

Response: As autonomous machines become increasingly prevalent in society, they must have the ability to forge cooperative relationships with people who do not share all of their preferences.  Unlike the zero-sum scenarios (e.g., Checkers, Chess, Go) often addressed by artificial intelligence, cooperation does not require sheer computational power.  Instead, it is facilitated by intuition, emotions, signals, cultural norms, and pre-evolved dispositions.  To understand how to create machines that cooperate with people, we developed an algorithm (called S#) that combines a state-of-the-art reinforcement learning algorithm with mechanisms for signals.

We compared the performance of S# with people in a variety of repeated games.

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