Peter Stone's Selected Publications

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Cobot in LambdaMOO: An Adaptive Social Statistics Agent

Charles Lee Isbell, Jr., Michael Kearns, Satinder Singh, Christian Shelton, Peter Stone, and Dave Kormann. Cobot in LambdaMOO: An Adaptive Social Statistics Agent. Autonomous Agents and Multiagent Systems, 13(3), November 2006.
Official version from publisher's website.
Contains material that was previously published in an Agents-2001 paper that won the BEST PAPER AWARD. JAAMAS

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Abstract

We describe our development of Cobot, a novel software agent who lives in LambdaMOO, a popular virtual world frequented by hundreds of users. Cobot's goal was to become an actual part of that community. Here, we present a detailed discussion of the functionality that made him one of the objects most frequently interacted with in LambdaMOO, human or artificial. Cobot's fundamental power is that he has the ability to collect social statistics summarizing the quantity and quality of interpersonal interactions. Initially, Cobot acted as little more than a reporter of this information; however, as he collected more and more data, he was able to use these statistics as models that allowed him to modify his own behavior. In particular, cobot is able to use this data to "self-program," learning the proper way to respond to the actions of individual users, by observing how others interact with one another. Further, Cobot uses reinforcement learning to proactively take action in this complex social environment, and adapts his behavior based on multiple sources of human reward. Cobot represents a unique experiment in building adaptive agents who must live in and navigate social spaces.

BibTeX Entry

@Article{JAAMAS06,
	author="Charles Lee Isbell and Jr. and Michael Kearns and Satinder Singh and Christian Shelton and Peter Stone and Dave Kormann",
        title="Cobot in {L}ambda{MOO}:  An Adaptive Social Statistics Agent",
	journal="Autonomous Agents and Multiagent Systems",
	volume="13",number="3",
	month="November",
	year="2006",
	abstract={
                  We describe our development of Cobot, a novel
                  software agent who lives in LambdaMOO, a popular
                  virtual world frequented by hundreds of
                  users. Cobot's goal was to become an actual part of
                  that community. Here, we present a detailed
                  discussion of the functionality that made him one of
                  the objects most frequently interacted with in
                  LambdaMOO, human or artificial. Cobot's fundamental
                  power is that he has the ability to collect social
                  statistics summarizing the quantity and quality of
                  interpersonal interactions. Initially, Cobot acted
                  as little more than a reporter of this information;
                  however, as he collected more and more data, he was
                  able to use these statistics as models that allowed
                  him to modify his own behavior. In particular, cobot
                  is able to use this data to "self-program," learning
                  the proper way to respond to the actions of
                  individual users, by observing how others interact
                  with one another. Further, Cobot uses reinforcement
                  learning to proactively take action in this complex
                  social environment, and adapts his behavior based on
                  multiple sources of human reward. Cobot represents a
                  unique experiment in building adaptive agents who
                  must live in and navigate social spaces.
	},
	wwwnote={Official version from <a href="http://www.springerlink.com/content/j1x71352841j4770/?p=8282dada6fa24e81b625081d48d5fb35&pi=2">publisher's website</a>.<br> Contains material that was previously published in an <a href="http://www.cs.utexas.edu/~pstone/Papers/2001agents/cobots.pdf">Agents-2001 paper</a> that won the <b>BEST PAPER AWARD</b>. <a href="http://www.kluweronline.com/issn/1387-2532">JAAMAS</a>},
}	

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