Role allocation and reallocation in multiagent teams

Nair, Ranjit; Tambe, Milind; Marsella, Stacy

doi:10.1145/860575.860664

Cited by 71 publications

(53 citation statements)

References 10 publications

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“…Role enactment is achieved either by allocation by the system developers that determine which available agent is the most adequate for a task, or is decided by the agents themselves. In both cases, analysis techniques are needed to support enactment decision, which compare and evaluate different role allocations [19]. The set of agents that at a given moment is active in an organization is called the population.…”

Section: An Organizational Frameworkmentioning

confidence: 99%

Exploring Congruence Between Organizational Structure and Task Performance: A Simulation Approach

Dignum

Sonenberg

2006

Coordination, Organizations, Institutions, and Norms in Multi-Agent Systems

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Abstract. Reorganization of the structure of an organization is a crucial issue in multi-agent systems that operate in an open, dynamic environment. Ideally, autonomous agents must be able to evaluate and decide the most appropriate organization given the environment conditions. That is, there is a need for dynamic reorganization of coordination structures. In this paper, we describe how simulation studies could help to determine whether and how reorganization should take place, and present a simulation scenario that can be used to evaluate the congruence, or fit, between organizational structure and task performance. Preliminary results using a simulation environment illustrate how one can explore triggers for reorganization and compare strategies.

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Section: An Organizational Frameworkmentioning

confidence: 99%

Exploring Congruence Between Organizational Structure and Task Performance: A Simulation Approach

Dignum

Sonenberg

2006

Coordination, Organizations, Institutions, and Norms in Multi-Agent Systems

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“…Solving the RMTDP for the optimal role-taking policy, assuming that the roleexecution policy is fixed, is highly intractable [28]. In general the globally optimal role-taking policy will be of doubly exponential complexity, and so we may be left no choice but to run a brute-force policy search, i.e.…”

Section: Extension For Explicit Coordinationmentioning

confidence: 99%

“…The key novelty of this branch-and-bound algorithm, which we discuss below, is how the we exploit the structure of the TOP in order to compute upper bounds for parent nodes. The other details of this algorithm can be found in [28].…”

Section: Pruning the Role Allocation Spacementioning

confidence: 99%

Coordinating Teams in Uncertain Environments: A Hybrid BDI-POMDP Approach

Nair

Tambe

2005

Lecture Notes in Computer Science

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Abstract. Distributed partially observable Markov decision problems (POMDPs) have emerged as a popular decision-theoretic approach for planning for multiagent teams, where it is imperative for the agents to be able to reason about the rewards (and costs) for their actions in the presence of uncertainty. However, finding the optimal distributed POMDP policy is computationally intractable (NEXPComplete). This paper is focussed on a principled way to combine the two dominant paradigms for building multiagent team plans, namely the "belief-desireintention" (BDI) approach and distributed POMDPs. In this hybrid BDI-POMDP approach, BDI team plans are exploited to improve distributed POMDP tractability and distributed POMDP-based analysis improves BDI team plan performance. Concretely, we focus on role allocation, a fundamental problem in BDI teams -which agents to allocate to the different roles in the team. The hybrid BDI-POMDP approach provides three key contributions. First, unlike prior work in multiagent role allocation, we describe a role allocation technique that takes into account future uncertainties in the domain. The second contribution is a novel decomposition technique, which exploits the structure in the BDI team plans to significantly prune the search space of combinatorially many role allocations. Our third key contribution is a significantly faster policy evaluation algorithm suited for our BDI-POMDP hybrid approach. Finally, we also present experimental results from two domains: mission rehearsal simulation and RoboCupRescue disaster rescue simulation. In the RoboCupRescue domain, we show that the role allocation technique presented in this paper is capable of performing at human expert levels by comparing with the allocations chosen by humans in the actual RoboCupRescue simulation environment.

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“…In some cases, human insight can result in better decisions (and hence better behavior) than would be achieved by following, typically sub-optimal, coordination algorithms. For example, allocating agents to tasks, taking into account potential future failures is extremely complex [10], however humans may have experience that allows them to rapidly make reasonable decisions that take into account future failures. In other cases, human experience or simply preference should be imposed on the way the team performs its tasks.…”

Section: Introductionmentioning

confidence: 99%

Safety in the Context of Coordination via Adjustable Autonomy

Scerri

Sycara

Tambe

2009

Safety and Security in Multiagent Systems

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Abstract. When large heterogeneous robot and agent teams operate in the real-world, it is essential that a human operator has overall control to ensure safety. However, giving an operator the required control is difficult due to the complexity of the activities such teams engage in and the infeasibility of simply stopping the team whenever human input is required. Our approach to interaction in such a context has three key components which allow us to leverage human expertise by giving them responsibility for key coordination decisions, without risks to the coordination due to slow responses. First, to deal with the dynamic nature of the situation, we use pre-planned sequences of transfer of control actions called transfer-of-control strategies. Second, to allow identification of key coordination issues in a distributed way, individual coordination tasks are explicitly represented as coordination roles, rather than being implicitly represented within a monolithic protocol. Such a representation allows meta-reasoning about those roles to determine when human input may be useful. Third, the meta-reasoning and transfer-of-control strategies are encapsulated in a mobile agent that moves around the group to either get human input or autonomously make a decision. In this paper, we describe this approach and present initial results from interaction between a large number of UAVs and a small number of humans.

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Role allocation and reallocation in multiagent teams

Cited by 71 publications

References 10 publications

Exploring Congruence Between Organizational Structure and Task Performance: A Simulation Approach

Exploring Congruence Between Organizational Structure and Task Performance: A Simulation Approach

Coordinating Teams in Uncertain Environments: A Hybrid BDI-POMDP Approach

Safety in the Context of Coordination via Adjustable Autonomy

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