The dMARS Architecture: A Specification of the Distributed Multi-Agent Reasoning System

d’Inverno, Mark; Lück, Michael; Georgeff, Michael P.; Kinny, David; Wooldridge, Michael

doi:10.1023/b:agnt.0000019688.11109.19

Cited by 121 publications

(62 citation statements)

References 33 publications

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“…First, it adopts an ad-hoc policy language to describe the configuration of a system; such a language does not offer the systematism of OWL-based KAOS, nor its reasoning capababilities; on the other hand, since it was purposely designed for the task, it is more concise. Second, in order to enforce management policy in a registry, Miles et al create an agent that processes the goals of the policy and the operations performed on the registry using the belief-desireintention model and its specific instantiations as the procedural reasoning system (PRS) and the distributed multiagent reasoning system (dMARS) [9]. As far as enforcement (i.e., execution) is concerned, both approaches have strong theoretical underpinning, respectively OWL-based reasoning and belief-desire-intention model.…”

Section: Discussion and Related Workmentioning

confidence: 99%

Behavioural specification of grid services with the KAoS policy language

Moreau

Bradshaw

Breedy

et al. 2005

CCGrid 2005. IEEE International Symposium on Cluster Computing and the Grid, 2005.

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Section: Discussion and Related Workmentioning

confidence: 99%

Behavioural specification of grid services with the KAoS policy language

Moreau

Bradshaw

Breedy

et al. 2005

CCGrid 2005. IEEE International Symposium on Cluster Computing and the Grid, 2005.

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“…[5]. They built a system in which the reasoning is done by the Distributed Multi Agent System (dMars) [4]. What is specific for their model is that each agent has a given threshold for the emotional gauge, and when this is passed, the belief that the agent feels that particular emotion is asserted.…”

Section: Personalitymentioning

confidence: 99%

Emotional Belief-Desire-Intention Agent Model: Previous Work And Proposed Architecture

Puica¹,

Florea²

2013

IJARAI

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Abstract-Research in affective computing shows that agents cannot be truly intelligent, nor believable or realistic without emotions. In this paper, we present a model of emotional agents that is based on a BDI architecture. We show how we can integrate emotions, resources and personality features into an artificial intelligent agent so as to obtain a human-like behavior of this agent. We place our work in the general context of existing research in emotional agents, with emphasis on BDI emotional models.

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“…Although many ad-hoc implementations of this interpreter have been applied to several domains, such as dMARS [27], the release of JADEX [28] has recently gained a quick acceptance. JADEX is an extension of JADE [29], which facilitates FIPA communications between agents, and it is widely used to implement intelligent and software agents.…”

Section: Bdi Descriptionmentioning

confidence: 99%

Data fusion to improve trajectory tracking in a Cooperative Surveillance Multi-Agent Architecture

2010

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In this paper we present an extension of Cooperative Surveillance Multi-Agent System (CS-MAS) architecture to incorporate dynamic coalition formation. A specific coalition formation using fusion skills is shown so that the fusion process is distributed now in two layers: (i) a global layer in the fusion center, which initialize the coalitions and (ii), local layer within coalitions, with the dynamic instantiation of a local fusion agent. There are several types of autonomous agents: surveillancesensor agents, fusion center agent, local fusion agent, interface agents, record agents, planning agents, etc. Autonomous agents differ in their ability to carry out a specific surveillance task. A surveillance-sensor agent controls and manages individual sensors (usually video cameras). It has different capabilities depending on its functional complexity and limitation related to specific sensor nature aspects. In this work we add a new autonomous agent called local fusion agent to the CS-MAS architecture, addressing specific problems of on-line sensor alignment, registration, bias removal and data fusion. The local fusion agent it is dynamically created by the fusion center agent and involves several surveillance-sensor agents working in a coalition. We show how the inclusion of this new dynamic local fusion agent guarantee that, in a video-surveillance system, objects of interest are successfully tracked across the whole area, assuring continuity and seamless transitions.

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The dMARS Architecture: A Specification of the Distributed Multi-Agent Reasoning System

Cited by 121 publications

References 33 publications

Behavioural specification of grid services with the KAoS policy language

Behavioural specification of grid services with the KAoS policy language

Emotional Belief-Desire-Intention Agent Model: Previous Work And Proposed Architecture

Data fusion to improve trajectory tracking in a Cooperative Surveillance Multi-Agent Architecture

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