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Multi-Agent Role Allocation: Issues, Approaches, and Multiple Perspectives
- AUTON AGENT MULTI-AGENT SYST
"... In cooperative multi-agent systems, roles are used as a design concept when creating large systems, they are known to facilitate specialization of agents, and they can help to reduce interference in multi-robot domains. The types of tasks that the agents are asked to solve and the communicative capa ..."
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In cooperative multi-agent systems, roles are used as a design concept when creating large systems, they are known to facilitate specialization of agents, and they can help to reduce interference in multi-robot domains. The types of tasks that the agents are asked to solve and the communicative capabilities of the agents significantly affect the way roles are used in cooperative multi-agent systems. Along with a discussion of these issues about roles in multi-agent systems, this article compares computational models of the role allocation problem, presents the notion of explicitly versus implicitly defined roles, gives a survey of the methods used to approach role allocation problems, and concludes with a list of open research questions related to roles in multi-agent systems.
A multi-layered semantics-ready sensor architecture
- Proceedings of the Third International Workshop on Agent Technology for Sensor Networks (ATSN-09
, 2009
"... There is an intrinsic tension between sensor systems and multi-agent systems that comes down to the trade-off between cost and value:1 the agents want as much knowledge of their environment as possible, while the sensors are rightly protective of their often very limited resources that enable sensin ..."
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There is an intrinsic tension between sensor systems and multi-agent systems that comes down to the trade-off between cost and value:1 the agents want as much knowledge of their environment as possible, while the sensors are rightly protective of their often very limited resources that enable sensing and transmission. The archi-tecture and implementation that we present here aims to provide sufficient flexibility for the cohabitation of both classes—where class is a relative term—of components through a policy-aware framework that permits the construction of “sensors ” at whatever level of abstraction is regarded as appropriate by the designer. There are many sensor architectures available, nevertheless we believe there is some novelty in the approach we present here in terms of systems engineering, deriving mainly from the principled design of Agentscape upon which we are building, such that the notable features are modularity—there is a high degree of separation of concerns—extensibility—leading to relative ease of integration of different sensor infrastructures—and scalability—as a result of the distributed architecture that Agentscape provides. In addition, our choice of RDF as the initial database format has positive practical implications for the integration of supported sensor networks with semantic processing mechanisms.
Article A Multi-Agent System Architecture for Sensor Networks
, 2009
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Management and control of energy usage and price using participatory sensing data
- In 3rd International Workshop on Agent Technologies for Energy Systems (ATES), at AAMAS 2012
, 2012
"... A key change in the move to Smart Grids (SGs) is the use of dynamic pricing; this together with less reliable energy from renewable resources makes optimising electricity use highly complex. For smart-devices to function in this envi-ronment, they must adapt to this complexity, while main-taining th ..."
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A key change in the move to Smart Grids (SGs) is the use of dynamic pricing; this together with less reliable energy from renewable resources makes optimising electricity use highly complex. For smart-devices to function in this envi-ronment, they must adapt to this complexity, while main-taining the flexibility to handle changing user behaviour pat-terns. Reinforcement Learning (RL) has been used to op-timise the scheduling of dynamic resources in SGs. It is proposed to provide smart-devices with knowledge of user intentions and actions by leveraging participatory sensing data. This, in consequence, will allow devices in the SG to tailor their operational schedule to users ’ behaviour. With-out this data, the devices ’ operation would be interrupted by user activity, leading to suboptimal results. Participa-tory sensing provides for both, the monitoring of parame-ters affecting devices operation (for example, temperature for a heating system) and access to detailed information about user behaviour and activity. The results obtained by our RL approach, clearly indicate that participatory sensing data indeed improve the performance of device scheduling when compared to static schemes resulting in a dramatic price reduction.
Multi-agent support in a middleware for mission-driven heterogeneous sensor networks
- The Computer Journal
, 2011
"... The emerging applications using sensor network technologies constitute a new trend requiring several different devices to work together and partly autonomously. However, the integration and coordination of heterogeneous sensors in these emerging systems is still a challenge, especially when the targ ..."
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The emerging applications using sensor network technologies constitute a new trend requiring several different devices to work together and partly autonomously. However, the integration and coordination of heterogeneous sensors in these emerging systems is still a challenge, especially when the target application scenario is susceptible to constant changes. The setup and adaptation of these systems are challenging, considering that their nodes are distributed and must respect operational constraints, such as energy consumption. Due to the dynamicity of the scenarios in which they are deployed and the nature of their operations these systems require autonomous decisions that have to be taken without any human operator intervention. This paper presents a reflective middleware that supports heterogeneous sensor networks deployed in dynamic scenarios. This middleware presents specific handling of users ’ requirements by representing them as missions that must be accomplished by the network. These missions are then translated to network parameters and activities that are distributed to network nodes by means of the autonomous reasoning that takes into account network nodes ’ capabilities and environment conditions. A multi-agent framework is proposed to provide the necessary support for missions ’ dissemination and for the required reasoning to allow autonomous
Integrating Jade and MAPS for the development of Agent-based WSN applications
"... Abstract Recent years have seen rapid advancements in wireless sensor networks (WSNs) and software agents resulting, among others, in maturation of their technol-ogy platforms. Furthermore, benefits of combining these research areas have been analyzed. The MAPS agent platform allows fusion of agents ..."
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Abstract Recent years have seen rapid advancements in wireless sensor networks (WSNs) and software agents resulting, among others, in maturation of their technol-ogy platforms. Furthermore, benefits of combining these research areas have been analyzed. The MAPS agent platform allows fusion of agents and WSN’s. However, due to the hardware limitation, MAPS misses important functionalities needed, for instance, in advanced decision support. Such functions are available, among oth-ers, in the JADE agent platform, geared towards more powerful computing devices. Therefore, integration of MAPS and JADE had to be considered. The aim of this paper is to discuss technical issues involved in achieving this goal. 1
Towards a Cloud-assisted and Agent-oriented Architecture for the Internet of Things
"... actuators, smart devices, smart objects, RFID, embedded computers, robots) have their identities, physical attributes, and interfaces. They will be seamlessly integrated into the information network such that they will become active participants in business, information and social processes wherever ..."
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actuators, smart devices, smart objects, RFID, embedded computers, robots) have their identities, physical attributes, and interfaces. They will be seamlessly integrated into the information network such that they will become active participants in business, information and social processes wherever and whenever needed and proper. The technical realization of this vision is a complex challenge as distributed heterogeneous IoT components at different levels of abstractions need to cooperate among themselves, with conventional networked IT infrastructures, and also with human users. To cope with this issue, we propose the synergic exploitation of two complementary mainstream paradigms for large-scale distributed computing: the agent-oriented and the cloud computing paradigms. While the former can support the development of decentralized, dynamic, cooperating and open IoT systems in terms of multi-agent systems, the latter can empower the IoT objects with more computing and memory resources and effectively support system-wide higher-level mechanisms and policies. In this paper, we introduce a cloud-assisted and agent-oriented vision for IoT based on layered reference architecture. Finally, we briefly overview our agent-oriented middleware for cooperating smart objects and a sensor-cloud infrastructure that represent the basic building blocks for technically achieving such vision.
An Organizational Design for Adaptive Sensor Networks°
"... As wireless sensor network applications grow in complexity, ad-hoc techniques are no longer adequate. Thus, it is crucial that these systems be adaptive and autonomous to remain functional in the face of unreliable communications, dead nodes, and other unexpected failures. We propose to manage senso ..."
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As wireless sensor network applications grow in complexity, ad-hoc techniques are no longer adequate. Thus, it is crucial that these systems be adaptive and autonomous to remain functional in the face of unreliable communications, dead nodes, and other unexpected failures. We propose to manage sensor networks based on a rigorous multiagent organizational design, which separates application logic from low-level sensor implementation details. The organizational design allows designers to specify high-level goals that the systems will try to achieve based on sensor capabilities. 1.
Multi-Agent Architecture for the Design of WSN Applications
, 2011
"... Complex and distributed systems are more and more associated with the application of WSN (Wireless Sensor Network) technology. The design of such applications presents important challenges and requires the assistance of several meth-odologies and tools. Multi-Agent systems (MAS) have been identified ..."
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Complex and distributed systems are more and more associated with the application of WSN (Wireless Sensor Network) technology. The design of such applications presents important challenges and requires the assistance of several meth-odologies and tools. Multi-Agent systems (MAS) have been identified as one of the most suitable technologies to con-tribute to this domain due to their appropriateness for modeling distributed and autonomous complex systems. This work aims to contribute in the help of the design of WSN applications. The proposed architecture exploits the advan-tages of MAS for modeling WSN services, network topologies and sensor device architectures.
1 Simulating BDI-based Wireless Sensor Networks
"... Abstract—“Autonomic systems ” merge advancements in the field of multi-agent software design, dynamic analysis, and decentralized control in order to assist designers in constructing complex distributed systems. Wireless Sensor Networks (WSN) represent such systems, and may benefit from autonomic sy ..."
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Abstract—“Autonomic systems ” merge advancements in the field of multi-agent software design, dynamic analysis, and decentralized control in order to assist designers in constructing complex distributed systems. Wireless Sensor Networks (WSN) represent such systems, and may benefit from autonomic system designs that target distributed nodes in diverse and changing environments that interact over a wireless communication channel for decentralized problem solving. Multi-agent system techniques have been recently applied to WSN’s; however, due to hardware limitations nodes (agents) are not fully deliberative (or strong) reasoning systems. Since hardware increases rapidly it is expected that such systems may eventually be viable. In this paper we provide a generic, extensible, and deliberative simulator for testing interactions in autonomous WSN’s. The belief, desire, intention (BDI) agent model of Rao is used, as well as the Agentspeak language, and the Jason framework. Results from two simple WSN test scenarios show how (simulated) BDI agents might perform basic WSN functions.
