2013
DOI: 10.1609/aaai.v27i1.8659
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Teamwork with Limited Knowledge of Teammates

Abstract: While great strides have been made in multiagent teamwork, existing approaches typically assume extensive information exists about teammates and how to coordinate actions. This paper addresses how robust teamwork can still be created even if limited or no information exists about a specific group of teammates, as in the ad hoc teamwork scenario. The main contribution of this paper is the first empirical evaluation of an agent cooperating with teammates not created by the authors, where the agent is not provi… Show more

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Cited by 33 publications
(17 citation statements)
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“…Recently, research efforts have been put on ad hoc interactions among agents, where agents need to interact without prior knowledge of the other agents (Stone et al 2010). They study both cooperative (Barrett et al 2013;Albrecht, Crandall, and Ramamoorthy 2016) and competitive (Southey et al 2012;Albrecht, Crandall, and Ramamoorthy 2016) scenarios, where agent type hypothesis and opponent modelling are used to handle the uncertainty. However, they do not consider the uncertainty in agent action observation and limited learning trials.…”
Section: Related Workmentioning
confidence: 99%
“…Recently, research efforts have been put on ad hoc interactions among agents, where agents need to interact without prior knowledge of the other agents (Stone et al 2010). They study both cooperative (Barrett et al 2013;Albrecht, Crandall, and Ramamoorthy 2016) and competitive (Southey et al 2012;Albrecht, Crandall, and Ramamoorthy 2016) scenarios, where agent type hypothesis and opponent modelling are used to handle the uncertainty. However, they do not consider the uncertainty in agent action observation and limited learning trials.…”
Section: Related Workmentioning
confidence: 99%
“…While pre-coordinated multiagent teams are well studied, there has been less research into teams in which this precoordination is not available. This work builds on the ideas of Barrett et al (2013), specifically learning about past teammates and using this knowledge to quickly adapt to new teammates. However, that work focused on a simpler domain in the form of a grid world, while this work investigates a complex, simulated robotics domain.…”
Section: Related Workmentioning
confidence: 99%
“…This section describes PLASTIC-Policy, shown in Algorithm 1. PLASTIC-Policy is an extension of the algorithm proposed by Barrett et al (2013). Compared to that work, the main differences are 1) the use of a policy-based, modelfree method rather than a model-based approach and 2) the evaluations are on the much more complex domain of HFO.…”
Section: Plastic-policymentioning
confidence: 99%
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“…However, in many domains we do not have such a model. The study of "ad-hoc" teamwork deals with multiagent teams with absence of information (Barrett et al 2013;Agmon and Stone 2012). They focus, however, on how a new agent must decide its behavior in order to cooperate with agents of unknown type, not on picking the best team.…”
Section: Related Workmentioning
confidence: 99%