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Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges

Patrick MacAlpine and Peter Stone. Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges. In AAMAS Multiagent Interaction without Prior Coordination (MIPC) Workshop, May 2017.

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Abstract

Ad hoc teamwork has been introduced as a general challenge for AI and especially multiagent systems. The goal is to enable autonomous agents to band together with previously unknown teammates towards a common goal: collaboration without pre-coordination. A long-term vision for ad hoc teamwork is to enable robots or other autonomous agents to exhibit the sort of flexibility and adaptability on complex tasks that people do, for example when they play games of "pick-up" basketball or soccer. As a testbed for ad hoc teamwork, autonomous robots have played in pick-up soccer games, called "drop-in player challenges", at the international RoboCup competition. An open question is how best to evaluate ad hoc teamwork performance---how well agents are able to coordinate and collaborate with unknown teammates---of agents with different skill levels and abilities competing in drop-in player challenges. This paper presents new metrics for assessing ad hoc teamwork performance, specifically attempting to isolate an agent's coordination and teamwork from its skill level, during drop-in player challenges. Additionally, the paper considers how to account for only a relatively small number of pick-up games being played when evaluating drop-in player challenge participants.

BibTeX

@InProceedings{MIPC17-MacAlpine,
  author = {Patrick MacAlpine and Peter Stone},
  title = {Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges},
  booktitle = {AAMAS Multiagent Interaction without Prior Coordination (MIPC) Workshop},
  location = {S\~ao Paulo, Brazil},
  month = {May},
  year = {2017},
  abstract={
Ad hoc teamwork has been introduced as a general challenge for AI and 
especially multiagent systems. The goal is to enable autonomous agents to band 
together with previously unknown teammates towards a common goal: collaboration 
without pre-coordination. A long-term vision for ad hoc teamwork is to enable 
robots or other autonomous agents to exhibit the sort of flexibility and 
adaptability on complex tasks that people do, for example when they play games 
of "pick-up" basketball or soccer. As a testbed for ad hoc teamwork, autonomous 
robots have played in pick-up soccer games, called "drop-in player challenges", 
at the international RoboCup competition. An open question is how best to 
evaluate ad hoc teamwork performance---how well agents are able to coordinate and 
collaborate with unknown teammates---of agents with different skill levels and 
abilities competing in drop-in player challenges. This paper presents new 
metrics for assessing ad hoc teamwork performance, specifically attempting to 
isolate an agent's coordination and teamwork from its skill level, during 
drop-in player challenges. Additionally, the paper considers how to account for 
only a relatively small number of pick-up games being played when evaluating 
drop-in player challenge participants.
  },
}

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