Peter Stone's Selected Publications

Classified by TopicClassified by Publication TypeSorted by DateSorted by First Author Last NameClassified by Funding Source


Expected Value of Communication for Planning in Ad Hoc Teamwork

William Macke, Reuth Mirsky, and Peter Stone. Expected Value of Communication for Planning in Ad Hoc Teamwork. In Proceedings of the 35th Conference on Artificial Intelligence (AAAI), February 2021.

Download

[PDF]869.9kB  [slides.pdf]2.3MB  [poster.pdf]1.8MB  

Abstract

A desirable goal for autonomous agents is to be able to coordinate on the fly with previously unknown teammates. Known as “ad hoc teamwork”, enabling such a capability has been receiving increasing attention in the research community. One of the central challenges in ad hoc teamwork is quickly recognizing the current plans of other agents and planning accordingly. In this paper, we focus on the scenario in which teammates can communicate with one another, but only at a cost. Thus, they must carefully balance plan recognition based on observations vs. that based on communication. This paper proposes a new metric for evaluating how similar are two policies that a teammate may be following - the Expected Divergence Point (EDP). We then present a novel planning algorithm for ad hoc teamwork, determining which query to ask and planning accordingly. We demonstrate the effectiveness of this algorithm in a range of increasingly general communication in ad hoc teamwork problems.

BibTeX Entry

@InProceedings{AAAI21-Macke,
  author = {William Macke and Reuth Mirsky and Peter Stone},
  title = {Expected Value of Communication for Planning in Ad Hoc Teamwork},
  booktitle = {Proceedings of the 35th Conference on Artificial Intelligence (AAAI)},
  location = {Virtual Conference},
  month = {February},
  year = {2021},
  abstract = {
	  A desirable goal for autonomous agents is to be able to coordinate 
	  on the fly with previously unknown teammates. Known as “ad hoc teamwork”, 
	  enabling such a capability has been receiving increasing attention in 
	  the research community. One of the central challenges in ad hoc teamwork is 
	  quickly recognizing the current plans of other agents and planning accordingly. 
	  In this paper, we focus on the scenario in which teammates can communicate 
	  with one another, but only at a cost. Thus, they must carefully balance 
	  plan recognition based on observations vs. that based on communication. 
	  This paper proposes a new metric for evaluating how similar are two policies 
	  that a teammate may be following  -  the Expected Divergence Point (EDP).  
	  We then present a novel planning algorithm for ad hoc teamwork, 
	  determining which query to ask and planning accordingly. We demonstrate the 
	  effectiveness of this algorithm in a range of increasingly general 
	  communication in ad hoc teamwork problems.
  },
}

Generated by bib2html.pl (written by Patrick Riley ) on Wed Jul 21, 2021 08:39:16