Demos

2014 ◽  
Vol 2 (4) ◽  
pp. 81-99 ◽  
Author(s):  
Nikolaos Bourbakis ◽  
Lefteri H. Tsoukalas ◽  
Miltiadis Alamaniotis ◽  
Rong Gao ◽  
K. Kerkman
Keyword(s):  
Knowledge Base ◽  
Intelligent Agents ◽  
Smart Cities ◽  
Dynamic Network ◽  
Distributed Model ◽  
Base System ◽  
Model Framework ◽  
Distributed Resources ◽  
Information Agents ◽  
Intelligent Information

In today's dynamic network environments like smart cities, information evolves in distributed resources and in different forms or modalities. An agent or a system that wants to be actively part of this evolution has to be interactive, adaptive, autonomous and intelligent. The paper presents a new version of a distributed model-framework (called Demos) based on autonomous, intelligent agents with anticipatory responses. The first version of the system was proposed by , and the new features (LG Graphs, SPNs and NNs) were embedded in the version presented here. The Demos model is mainly based on the development of an adaptive distributed knowledge base system. Knowledge is represented in a form of frames with internal stochastic Petri-net graph for local representations (KR). A major advantage for the Demos model having a distributed (possibly across the net) is the adaptive knowledge base. Here the authors present the design of an adaptive knowledge model and its challenge, which lays principally on how to learn new knowledge by synthesising SPN forms, and how to develop anticipatory responses at an agent's site. The development of the Demos prototype has a great range of applicability, such as in autonomous negotiating teams, autonomous distributed units for energy efficient distribution, autonomous multiple mobile robots space exploration and maps generation, autonomous intelligent information agents (WWW), automatic information synthesis and fusion, etc. Here the authors have used this model for management of the electric power on a grid of a smart city.

Design and implementation of ontology-based knowledge base system for marine hydrocarbon geology

2010 ◽  
Vol 30 (2) ◽  
pp. 532-536
Author(s):  
Guo-he LI ◽  
Xin-ying YANG ◽  
Ting YE ◽  
Hong-jun SUN ◽  
Xian-ming TANG ◽  
...  
Keyword(s):  
Knowledge Base ◽  
Base System ◽  
Design And Implementation ◽  
Knowledge Base System

A Web-Enabled, Mobile Intelligent Information Technology Architecture for On-Demand and Mass Customized Markets

2010 ◽  
pp. 83-123
Author(s):  
M. Ghiassi ◽  
C. Spera
Keyword(s):  
Information System ◽  
Supply Chain ◽  
Intelligent Agents ◽  
Simulated Data ◽  
General Purpose ◽  
Cost Overruns ◽  
On Demand ◽  
Intelligent Information ◽  
Improving Accuracy ◽  
Event Based

This chapter presents a web-enabled, intelligent agent-based information system model to support on-demand and mass customized markets. The authors present a distributed, real-time, Java-based, mobile information system that interfaces with firms’ existing IT infrastructures, follows a build-to-order production strategy, and integrates order-entry with supply chain, manufacturing, and product delivery systems. The model provides end-to-end visibility across the entire operation and supply chain, allows for a collaborative and synchronized production system, and supports an event-based manufacturing environment. The system introduces four general purpose intelligent agents to support the entire on-demand and mass customization processes. The adoption of this approach by a semiconductor manufacturing firm resulted in reductions in product lead time (by half), buffer inventory (from five to two weeks), and manual transactions (by 80%). Application of this approach to a leading automotive manufacturer, using simulated data, resulted in a 51% total inventory reduction while increasing plant utilization by 30%. Adoption of this architecture by a pharmaceutical firm resulted in improving accuracy of trial completion estimates from 74% to 82% for clinical trials resulting in reduced trial cost overruns. These results verify that the successful adoption of this system can reduce inventory and logistics costs, improve delivery performance, increase manufacturing facilities utilization, and provide a higher overall profitability.

Multiagent Systems in the Web

2011 ◽  
pp. 2734-2740
Author(s):  
Hércules Antonio do Prado ◽  
Aluizio Haendchen Filho ◽  
Míriam Sayão ◽  
Edilson Ferneda
Keyword(s):  
Information Systems ◽  
Multiagent Systems ◽  
Business Processes ◽  
Distributed Database ◽  
Information Resources ◽  
Full Potential ◽  
Information Agents ◽  
Extensible Markup ◽  
Intelligent Information ◽  
The Web

The rapid evolution of Internet has opened a new era in the distributed systems scenery: the bigger part of the information systems currently developed is focused in Web applications. Typically, the information resources in Web systems are dynamic, distributed, and heterogeneous. Since these computing environments are opened, information resources can be connected or disconnected at any time. This ubiquity of Web and its distributed and interconnected characteristics represent a natural field for multiagent systems (MAS), spreading this kind of application. Software agents can dynamically discover, orchestrate, and compose services, check activities, run business processes, and integrate heterogeneous applications. Most of the large organizations adopt heterogeneous and complex information systems. These systems must coordinate their applications in order to provide efficient support to business processes and consistent information management. Unfortunately, the operational software underlying these systems usually does not handle multitask distributed heterogeneous applications. Currently, enterprises are strongly interested in the strategic advantages of adopting distributed infrastructures that are designed to be dynamic, flexible, adaptable, and interoperable. In this context, the demand for agent-based applications has increased, opening new types of applications that include e-commerce, Web services, knowledge management, semantic Web, and information systems in general. Interesting solutions to B2B (business to business), e-business, and also applications that require interoperability based on knowledge about applications and business processes, will definitely benefit from the MAS technology. Also, intelligent information agents are regarded as one of the most promising areas for applying agents’ technology. Intelligent information agents act in fields like collaborative systems on Internet, knowledge discovery from heterogeneous sources, systems for intelligent management of information, and so on. The Web can also be seen as a big distributed database having XML (extensible markup language) and its extensions or modifications as an underlying data model. In this context, the MAS development has received support from new tools in order to make it easier for the developer to cope with specific requirements for Web architectures. It is accepted that these improvements in the technology, mainly by the new tools that are becoming available, will lead MAS technology to be explored in its full potential. So, we can state that the application domain of MAS is going to be strongly enlarged, defining a turning point in the systems development activity. In this chapter, we provide an overview on MAS technology, discuss how this technology is impacting the Web context, and provide a sound description of the concepts that are relevant to the application developers and target users.

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