Asimovian multiagents: applying laws of robotics to teams of humans and agents

  • Authors:

  • Nathan Schurr;Pradeep Varakantham;Emma Bowring;Milind Tambe;Barbara Grosz

  • Affiliations:

  • Computer Science Department, University of Southern California, Los Angeles, California;Computer Science Department, University of Southern California, Los Angeles, California;Computer Science Department, University of Southern California, Los Angeles, California;Computer Science Department, University of Southern California, Los Angeles, California;Harvard University, Maxwell-Dworkin Laboratory, Cambridge, MA

  • Venue:
  • ProMAS'06 Proceedings of the 4th international conference on Programming multi-agent systems
  • Year:
  • 2006

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Abstract

In the March 1942 issue of "Astounding Science Fiction", Isaac Asimov for the first time enumerated his three laws of robotics. Decades later, researchers in agents and multiagent systems have begun to examine these laws for providing a useful set of guarantees on deployed agent systems. Motivated by unexpected failures or behavior degradations in complex mixed agent-human teams, this paper for the first time focuses on applying Asimov's first two laws to provide behavioral guarantees in such teams. However, operationalizing these laws in the context of such mixed agent-human teams raises three novel issues. First, while the laws were originally written for interaction of an individual robot and an individual human, clearly, our systems must operate in a team context. Second, key notions in these laws (e.g. causing "harm" to humans) are specified in very abstract terms and must be specified in concrete terms in implemented systems. Third, since removed from science-fiction, agents or humans may not have perfect information about the world, they must act based on these laws despite uncertainty of information. Addressing this uncertainty is a key thrust of this paper, and we illustrate that agents must detect and overcome such states of uncertainty while ensuring adherence to Asimov's laws. We illustrate the results of two different domains that each have different approaches to operationalizing Asimov's laws.