Task Decomposition and Dynamic Role Assignment for Real - Time Strategic Teamwork

Stone, Peter; Veloso, Manuela

doi:10.1007/3-540-49057-4_19

Cited by 73 publications

(64 citation statements)

References 16 publications

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“…Esteva et al [16] and Dignum [14] introduce the notion of norms in combination with the agent roles already used by Odell et al [33], Ferber and Gutknecht [17] and Wooldridge [47]. Roles can be used to decompose the tasks to be performed by the MAS into sub-objectives to increase efficiency [44,18,42]. The role-based approach to ad hoc teamwork by Genter et al [18] determines role selection on the team's utility.…”

Section: Related Researchmentioning

confidence: 99%

A Formalization of the Coach Problem

Schropp

Meyer

Ramamoorthy

2015

RoboCup 2014: Robot World Cup XVIII

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Abstract. Coordination is an important aspect of multi-agent teamwork. In the context of robot soccer in the RoboCup Standard Platform League, our focus is on the coach as an external observer of the team, aiming to provide his teammates with effective tactical advice during matches. The coach problem can be approached from different angles: in order to adapt the behaviour of his teammates, he should at first be able to perform plan recognition on their observable actions. Furthermore, in providing them with appropriate advice, he should still adhere to the norms and regulations of the match to prevent penalties for his team. Also, when teammates' profiles and attributes are unknown or the system is only partially observable, coordination should be more 'ad hoc' to ensure robustness of the Multi-Agent System (MAS). In this work, we present a formalization of the problem of designing a coach in robot soccer, employing a temporal deontic logical framework. The framework is based on agent organizations [14], in which social coordination and norms play an important part.

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Section: Related Researchmentioning

confidence: 99%

A Formalization of the Coach Problem

Schropp

Meyer

Ramamoorthy

2015

RoboCup 2014: Robot World Cup XVIII

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“…For open play, CAMBADA uses an implicit coordination model based on notions like strategic positioning, role and formation. These notions and related algorithms have been introduced and/or extensively explored in the RoboCup Soccer Simulation League (Reis et al, 2001;Stone and Veloso, 1999). In order to apply such algorithms in the MSL, several changes had to be introduced.…”

Section: Coordination and Strategymentioning

confidence: 99%

CAMBADA Soccer Team: from Robot Architecture to Multiagent Coordination

Neves¹,

Azevedo²,

Cunha³

et al. 2010

Robot Soccer

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“…In a team situation, these individual policies can be used to describe a player's role in the team (e.g., combat medic). A team policy is an allocation of players to these tactical roles and is typically arranged prior to the scenario as a locker-room agreement [89]. However, circumstances during the battle (such as the elimination of a teammate or unexpected enemy reinforcements) can frequently force players to take actions that were a priori lower in their individual preference model.…”

Section: Problem Formulationmentioning

confidence: 99%

Activity Recognition for Agent Teams

Sycara

Sukthankar

2007

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Proficient teams can accomplish goals that would not otherwise be achievable by groups of uncoordinated individuals. This thesis addresses the problem of analyzing team activities from external observations and prior knowledge of the team's behavior patterns. There are three general classes of recognition cues that are potentially valuable for team activity/plan recognition: (1) spatial relationships between team members and/or physical landmarks that stay fixed over a period of time; (2) temporal dependencies between behaviors in a plan or between actions in a behavior; (3) coordination constraints between agents and the actions that they are performing. This thesis examines how to leverage available spatial, temporal, and coordination cues to perform offline multi-agent activity/plan recognition for teams with dynamic membership.In physical domains (military, athletic, or robotic), team behaviors often have an observable spatio-temporal structure, defined by the relative physical positions of team members and their relation to static landmarks. We suggest that this structure, along with temporal dependencies and coordination constraints defined by a team plan library, can be exploited to perform behavior recognition on traces of agent activity over time, even in the presence of uninvolved agents. Unlike prior work in team plan recognition where it is assumed that team membership stays constant over time, this thesis addresses the novel problem of recovering agent-to-team assignment for team tasks where team composition, the mapping of agents into teams, changes over time; this allows the analysis of more complicated tasks in which agents must periodically divide into subteams.This thesis makes four main contributions: (1) an efficient and robust technique for formation identification based on spatial relationships; (2) a new algorithm for simultaneously determining team membership and performing behavior recognition on spatio-temporal traces with dynamic team membership; (3) a general pruning technique based on coordination cues that improves the efficiency of plan recognition for dynamic teams; (4) methods for identifying player policies in team games that lack strong spatial, temporal, and coordination dependencies.ii

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Task Decomposition and Dynamic Role Assignment for Real - Time Strategic Teamwork

Cited by 73 publications

References 16 publications

A Formalization of the Coach Problem

A Formalization of the Coach Problem

CAMBADA Soccer Team: from Robot Architecture to Multiagent Coordination

Activity Recognition for Agent Teams

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