Building Agent Service Oriented Multi-Agent Systems

2007 ◽  
pp. 11-20 ◽  
Author(s):  
Dan Luo ◽  
Longbing Cao ◽  
Jiarui Ni ◽  
Li Liu
Keyword(s):  
Multi Agent Systems ◽  
Agent Systems ◽  
Service Oriented ◽  
Multi Agent

An overview of search strategies in distributed environments

2013 ◽  
Vol 29 (3) ◽  
pp. 281-313 ◽  
Author(s):  
E. Del Val ◽  
M. Rebollo ◽  
V. Botti
Keyword(s):  
Dynamic Environments ◽  
System Structure ◽  
Search Process ◽  
Global Information ◽  
Distributed Environments ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Service Oriented ◽  
Multi Agent ◽  
Proper Performance

AbstractDistributed systems are populated by a large number of heterogeneous entities that join and leave the systems dynamically. These entities act as clients and providers and interact with each other in order to get a resource or to achieve a goal. To facilitate the collaboration between entities, the system should provide mechanisms to manage the information about which entities or resources are available in the system at a certain moment, as well as how to locate them in an efficient way. However, this is not an easy task in open and dynamic environments where there are changes in the available resources and global information is not always available. In this paper, we present a comprehensive vision of search in distributed environments. This review not only considers the approaches of the peer-to-peer area, but also the approaches from three more areas: service-oriented environments, multi-agent systems, and complex networks. In these areas, the search for resources, services, or entities plays a key role for the proper performance of the systems built on them. The aim of this analysis is to compare approaches from these areas taking into account the underlying system structure and the algorithms or strategies that participate in the search process.

The M3 Architecture for Smart Spaces

2017 ◽  
pp. 29-48
Keyword(s):  
Theoretical Background ◽  
Smart Environments ◽  
Multi Agent Systems ◽  
Smart Spaces ◽  
Generic Properties ◽  
Agent Systems ◽  
Space Design ◽  
Service Oriented ◽  
Multi Agent ◽  
Generic Design

In accordance with the previous chapter, a particular class of smart environments is created by Smart Spaces, where many devices participate using information-driven and ontology-oriented interaction. In this case, a smart space is developed based on models from multi-agent systems and knowledge manipulation technologies from the Semantic Web. In this chapter, we consider this particular approach for creating such smart environments. The M3 architecture (multidevice, multivendor, multidomain) aims at development of smart spaces that host advanced service-oriented applications. We introduce the theoretical background of the M3 architecture in respect to its open source implementation—the Smart-M3 platform. The latter forms a technology for creating M3-based smart spaces (M3 spaces) as heterogeneous dynamic multi-agent systems with multi-device, multi-vendor, multi-domain devices and services. We further consider the concept models of space computing that enable the studied class of smart spaces, derive the generic properties that an M3 space design requires, and describe the basic software components of M3 architecture that realize the generic design properties in accordance with the concept models.

Extending the JADE Framework for Semantic Peer-To-Peer Service Based Applications

2010 ◽  
pp. 18-35
Author(s):  
Agostino Poggi ◽  
Michele Tomaiuolo
Keyword(s):  
Distributed Systems ◽  
Peer To Peer ◽  
Legacy Systems ◽  
Software Framework ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Service Oriented ◽  
Multi Agent

One of the main challenges of multi-agent systems is to become the main means to support legacy systems interoperability and to make the realization of scalable distributed systems easy. In the last years, however, two technologies, peer-to-peer and service-oriented, have made an impressive progress and seem to have good chances of competing with multi-agent systems for the realization of scalable and interoperable systems. Conversely, neither of these two technologies is able to provide by themselves the autonomy and social and proactive capabilities of agents and thus the development of flexible adaptive distributed systems may be difficult. This chapter shows how JADE, one of the most known and used software framework for the development of multi-agent systems, has been extended with these technologies both to support the realization of multi-agent systems and to facilitate the interoperability with peer-to-peer and service-oriented systems.

Web Services Integration in Multi-Agent Systems

2010 ◽  
pp. 1-17
Author(s):  
Davide Guidi ◽  
Mauro Gaspari ◽  
Giuseppe Profiti
Keyword(s):  
Web Services ◽  
Autonomous Agents ◽  
Building Blocks ◽  
Multi Agent Systems ◽  
Fully Integrated ◽  
Agent Systems ◽  
Services Integration ◽  
Service Oriented ◽  
Multi Agent ◽  
Web Infrastructure

The development of distributed systems is influenced by several paradigms. For example, in the last few years, great emphasis has been placed on Service Orientation. In addition, technologies such as Web services are now considered standard, deployed in common development tools and widely used. However, despite this recent trend, the constantly growing number of powerful personal devices will inevitably revitalize the interest in another paradigm known as Autonomous Agents. Agents are in fact considered one of the main building blocks of the emerging next generation Web infrastructure. Web services are very important resources for agents. Agents should be able to retrieve, execute and compose Web services, providing an intelligent and personalized support to users. On the other hand, agents should also be able to export their functionalities as Web services in order to be fully integrated in the Service Oriented paradigm. In this chapter we present a survey of the current state of the art about Web services integration in open Multi-Agent Systems (MAS). Considering these approaches, we identify a set of requirements needed to achieve full integration and we present a communication infrastructure, which satisfies these requirements.

Control of Crisis Environments by the Use of WSN Structures and Based on Expert-SOA Architecture

2011 ◽  
Vol 383-390 ◽  
pp. 4629-4633
Author(s):  
Zahra Oladi Ghadikolaie ◽  
Sara Jafari Bazminabadi ◽  
Samira Kalantari ◽  
Zahra Hadjian Line ◽  
Shahaboddin Shamshirband
Keyword(s):  
Wireless Sensor Networks ◽  
Service Oriented Architecture ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Human Agent ◽  
Central Controller ◽  
Service Oriented ◽  
Multi Agent

In this article service-oriented architecture is implemented in crisis environments (such as in a place on fire). Our purpose is to use wireless sensor networks and multi-agent systems in crisis environments to gather information from the environment. This information is received by sensor nodes, it is then processed in the expert system, the deductions concerning the environment from which information has been gather are sent to the central controller, and then the central controller sends the messages to the human agent who becomes aware of the situation in the environment in order to carry out the prescribed duties.

scholarly journals Odor Classification using Agent Technology

2014 ◽  
Vol 2 (4) ◽  
pp. 41-48
Author(s):  
Sigeru Omatu ◽  
Tatsuyuki Wada ◽  
Pablo Chamoso
Keyword(s):  
Intelligent Agents ◽  
Quartz Crystal ◽  
Classification Systems ◽  
Multi Agent Systems ◽  
Agent Platform ◽  
Agent Systems ◽  
Service Oriented ◽  
Multi Agent ◽  
Odor Classification ◽  
New Algorithms

In order to measure and classify odors, Quartz Crystal Microbalance (QCM) can be used. In the present study, seven QCM sensors and three different odors are used. The system has been developed as a virtual organization of agents using an agent platform called PANGEA (Platform for Automatic coNstruction of orGanizations of intElligent Agents). This is a platform for developing open multi-agent systems, specifically those including organizational aspects. The main reason for the use of agents is the scalability of the platform, i.e. the way in which it models the services. The system models functionalities as services inside the agents, or as Service Oriented Approach (SOA) architecture compliant services using Web Services. This way the adaptation of the odor classification systems with new algorithms, tools and classification techniques is allowed.

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