Multiagent systems (MAS) development frameworks aim at facilitating the development and administration of agent-based applications. Currently relevant tools, such as JADE, offer huge possibilities but they are general...
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Multiagent systems (MAS) development frameworks aim at facilitating the development and administration of agent-based applications. Currently relevant tools, such as JADE, offer huge possibilities but they are generally linked to a specific technology (commonly Java). This fact may limit some application domains when deploying MAS, such as low efficiency or programming language restrictions. To contribute to the evolution of multiagent development tools and to overcome these constraints, we introduce a multiagent platform based on the FIPA standards and built on top of a modern object-oriented middle-ware. Experimental results prove the scalability and the short response-time of the proposal and justify the design and development of modern tools to contribute the multiagent technology. (C) 2009 Elsevier Inc. All rights reserved.
A reusable agent is a self-contained computational system that implements some specific expertise and that can be embedded into diverse applications requiring that expertise. Systems composed of heterogeneous reusable...
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A reusable agent is a self-contained computational system that implements some specific expertise and that can be embedded into diverse applications requiring that expertise. Systems composed of heterogeneous reusable agents are potentially highly adaptable, maintainable, and affordable, assuming that integration issues such as information sharing, coordination, and conflict management can be effectively addressed. In this article, we investigate sharing metalevel search information to improve system performance, specifically with respect to how sharing affects the quality of solutions and the runtime efficiency of a reusable-agent system. We first give a formal description of shareable metainformation in systems where agents have private knowledge and databases and where agents are specifically intended to be reusable. We then present and analyze experimental results from a mechanical design system for steam condensers that demonstrate performance improvements related to information sharing and assimilation. Finally, we discuss the practical benefits and limitations of information sharing in application systems comprising heterogeneous reusable agents. Issues of pragmatic interest include determining what types of information can realistically be shared and determining when the costs of sharing outweigh the benefits.
Management of complexity, changes and disturbances is one of the key issues of production today. distributed, agent-based structures represent viable alternatives to hierarchical systems provided with reactive/proacti...
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Management of complexity, changes and disturbances is one of the key issues of production today. distributed, agent-based structures represent viable alternatives to hierarchical systems provided with reactive/proactive capabilities. In the paper, approaches to distributed manufacturing architectures are surveyed, and their fundamental features are highlighted, together with the main questions to be answered while designing new structures. Moreover, an object-oriented simulation framework for development and evaluation of multi-agent manufacturing architectures is introduced. (C) 1998 Chapman & Hall.
Whereas an Intercloud is an interconnected global "cloud of clouds" that enables each cloud to tap into resources of other clouds, interactions among Intercloud stakeholders are complex because Intercloud re...
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Whereas an Intercloud is an interconnected global "cloud of clouds" that enables each cloud to tap into resources of other clouds, interactions among Intercloud stakeholders are complex because Intercloud resources are distributed and controlled by different clouds. "Agent-based cloud computing" involves the construction of agents for bolstering discovery, matching, selection, composition, negotiation, scheduling, workflow, and monitoring of Intercloud resources. An agent is a computer system that is capable of making decisions independently and interacting with other agents through cooperation, coordination, and negotiation. Using an agent-based approach, characteristics associated with intelligent behaviors of agents such as interacting socially through cooperation, coordination, and negotiation can be built into clouds. This survey 1) discusses the significance and advantages of using an agent paradigm for Intercloud resource allocation, 2) reviews representative models of agent-based Intercloud resource allocation and provides a comparison among these models, 3) compares agent-based and non-agent-based approaches for task executions in multiple clouds, and 4) provides pointers to future directions.
The agents and multiagent systems technology is actively researched by the academia and industrial community. However, the technology is particularly popular in the manufacturing domain, while the applications in othe...
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The agents and multiagent systems technology is actively researched by the academia and industrial community. However, the technology is particularly popular in the manufacturing domain, while the applications in other domains of industrial control are scarce. This survey focuses exclusively on the technology applications in the automation of continuous industrial processes, as the differences in the technology adoption between the process automation and manufacturing are significant. A large part of the literature on the subject is reviewed. The analysis of the literature is provided from several points of view, the main trends of research are described, including the shift of the researchers' interest from the agent-based supervisory control to the low-level agent-based control algorithms. Conclusions are provided regarding the lack of the technology support on the part of control instrumentation vendors;probable directions of the development are indicated, which turn out to be especially promising in the domain of biotechnological processes.
This paper presents a novel formulation of the configuration-design problem that achieves the benefits of the concurrent engineering (CE) design paradigm. In CE, all design concerns (manufacturability, testability, et...
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This paper presents a novel formulation of the configuration-design problem that achieves the benefits of the concurrent engineering (CE) design paradigm. In CE, all design concerns (manufacturability, testability, etc.) are applied to an evolving design throughout the design cycle. CE identifies conflicts early on, avoids costly redesign, and leads to better products. Our formulation is based on a distributed dynamic interval constraint-satisfaction problem (DDICSP) model. Persistent catalog agents map onto DDICSP variables and constraint agents map onto DDICSP constraints. These agents use a set of operations and heuristics to navigate the design space to eliminate sets of designs until a solution is found. Experimental results show that an architecture where each catalog agent resides on a separate computer has performance advantages over nondistributed approaches.
Shifting matrix management (SMM) is a model of agent coordination inspired by Mintzberg's model of organizational structures. Mintzberg's model permits many temporary lines of authority, reflecting the multipl...
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Shifting matrix management (SMM) is a model of agent coordination inspired by Mintzberg's model of organizational structures. Mintzberg's model permits many temporary lines of authority, reflecting the multiple and shifting functions of a flexible workforce. In order to apply these ideas to agent cooperation, a six-stage framework has been devised. The resulting model has been compared with two standard models: Contract Nets and Cooperative Problem-Solving. All three models have been implemented by means of an in-house blackboard system, Algorithmic and Rule-based Blackboard System (ARBS). 'Disembodied' agents have been constructed whose components are spread between system modules, known as knowledge sources, and private partitions of the blackboard. Tests have been carried out in which the three models have been applied to a set of tasks involving the control of two robots. Within the narrow context of these tests, the SMM model out-performs the other two approaches in terms of its task completion rate, number of tasks completed, and avoidance of wasted efforts. It is argued that although the SMM model expends more time reasoning about its actions, this is likely to be more than offset by the resultant efficient use of resources. (C) 2003 Elsevier Ltd. All rights reserved.
Swarm intelligence is a rapidly growing branch of artificialintelligence with numerous heuristics being developed. These offer faster and more accurate ways to achieve good solutions. Ant colony optimization (ACO) an...
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Swarm intelligence is a rapidly growing branch of artificialintelligence with numerous heuristics being developed. These offer faster and more accurate ways to achieve good solutions. Ant colony optimization (ACO) and particle swarm optimization (PSO) are the most common metaheuristics. Based on the behaviour of collectives of ants, birds, fish and others, they offer algorithms which can be used to solve different NP-hard problems. Multi-agent systems (MAS) offer new perspectives on organisation of code into specific components as autonomic, decentralized or distributed agents. The Multi-agent Systems Engineering (MaSE) methodology allows the combination of both aforementioned approaches. This paper presents research based on the AgentSwarm application which evaluates the efficiency of applying MaSE methodology to solve the traveling salesman problem (TSP) using ACO and PSO metaheuristics. Initial results have shown that MaSE is a comprehensive methodology, solid and reliable in building and developing swarm-based multi-agent systems.
Resource allocation problems aim to achieve certain goals or objectives by allocating resources. Traditionally. centralized methods are applied to Such problems. However, the inherent, decentralized nature of many cor...
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Resource allocation problems aim to achieve certain goals or objectives by allocating resources. Traditionally. centralized methods are applied to Such problems. However, the inherent, decentralized nature of many corporates/companies/factories drives the investigation on decentralized or distributed methods. This paper provides an overview of research activities in the field of distributed methods for resource allocation problems. We concentrate oil classifying the resource allocation problems, comparing different methods and discussing how these different methods can be applied to the problems. Finally, a range of open issues and future challenges are highlighted.
Green computing of stochastic nonlinear heterogeneous super-systems, represented by the cloud, is a new demand for sustainable human developments. However, the scheduling middleware is now in urgent need of a series o...
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Green computing of stochastic nonlinear heterogeneous super-systems, represented by the cloud, is a new demand for sustainable human developments. However, the scheduling middleware is now in urgent need of a series of theoretical breakthroughs from homogeneity to heterogeneity, linearity to non-linearity, and even fuzzy decision-making to scientific decision-making based on mathematical model. Focusing on deep fusion of hardware-software energy-saving principles, an energy-aware intelligent scheduling model and algorithm are proposed in this paper;throughout the stages of model preparation, composition and algorithm designs, three features and innovations are included, which are formalizing hardware energy-saving principles via nonlinear regression quantization, a comprehensive evaluation model of adaptive green scheduling for stochastic nonlinear heterogeneous super-systems, and a scheduling algorithm with distributed evolutionary intelligence. Extensive simulator and simulation experiments highlight obvious superiorities in the proposed scheduler such as higher efficacy and better scalability, which fully considers nonlinear diversities of heterogeneous super-systems whether for data or computing intensive stochastic tasks.
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