Battlefield visualization and intelligent agents decision support

2003 ◽  
Author(s):  
F. Mello ◽  
E. Strauss ◽  
A. Oliveira
Keyword(s):  
Decision Support ◽  
Intelligent Agents

Intelligent Agents in Decision Support Systems

2011 ◽  
pp. 857-866 ◽  
Author(s):  
Gloria E Phillips-Wren
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Intelligent Agents ◽  
Intelligent Systems ◽  
Information Overload ◽  
Support Systems ◽  
Distributed Decision Making ◽  
Intelligent Decision ◽  
Intelligent Decision Support Systems

Internet-based, distributed systems have become essential in modern organizations. When combined with artificial intelligence (AI) techniques such as intelligent agents, such systems can become powerful aids to decision makers. These newer intelligent systems have extended the scope of traditional decision support systems (DSSs) to assist users with real-time decision making, multiple information flows, dynamic data, information overload, time-pressured decisions, inaccurate data, difficult-to-access data, distributed decision making, and highly uncertain decision environments. As a class, they are called intelligent decision support systems (IDSSs).

Multi-Agent Architecture for Knowledge-Driven Decision Support

2010 ◽  
pp. 28-46
Author(s):  
Rahul Singh
Keyword(s):  
Decision Support ◽  
Intelligent Agents ◽  
Agent Architecture ◽  
Specific Knowledge ◽  
Domain Specific ◽  
Knowledge Based ◽  
Intelligent Software Agents ◽  
Intelligent Decision ◽  
Domain Specific Knowledge ◽  
Multi Agent

Organizations use knowledge-driven systems to deliver problem-specific knowledge over Internet-based distributed platforms to decision-makers. Increasingly, artificial intelligence (AI) techniques for knowledge representation are being used to deliver knowledge-driven decision support in multiple forms. In this chapter, we present an Architecture for knowledge-based decision support, delivered through a Multi-Agent Architecture. We illustrate how to represent and exchange domain-specific knowledge in XML-format through intelligent agents to create exchange and use knowledge to provide intelligent decision support. We show the integration of knowledge discovery techniques to create knowledge from organizational data; and knowledge repositories (KR) to store, manage and use data by intelligent software agents for effective knowledge-driven decision support. Implementation details of the architecture, its business implications and directions for further research are discussed.

Intelligent Agents for Decision Support

1998 ◽  
Vol 31 (29) ◽  
pp. 94-97
Author(s):  
Patrick Race ◽  
Jason Tedor ◽  
Kata L. Nance
Keyword(s):  
Decision Support ◽  
Intelligent Agents

Intelligent Agents in Decision Support Systems

2011 ◽  
pp. 505-513 ◽  
Author(s):  
Gloria E. Phillips-Wren
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Intelligent Agents ◽  
Intelligent Systems ◽  
Information Overload ◽  
Support Systems ◽  
Distributed Decision Making ◽  
Intelligent Decision ◽  
Intelligent Decision Support Systems

Internet-based, distributed systems have become essential in modern organizations. When combined with artificial intelligence (AI) techniques such as intelligent agents, such systems can become powerful aids to decision makers. These newer intelligent systems have extended the scope of traditional decision support systems (DSSs) to assist users with real-time decision making, multiple information flows, dynamic data, information overload, time-pressured decisions, inaccurate data, difficult-to-access data, distributed decision making, and highly uncertain decision environments. As a class, they are called intelligent decision support systems (IDSSs).

scholarly journals Agent based Decision Support System for Travelers

2020 ◽  
pp. 293-298
Author(s):  
Thi Thi Tun ◽  
Prof Thwe
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Information Systems ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Intelligent Agents ◽  
Decision Making Process ◽  
Agent Based ◽  
Travel Planning

Nowadays, management of the travelers to support their recreation or holiday planning is increasingly becoming important and popular. Planning a trip needs to assemble a wide variety of information from a large number of sources, such as car schedule and prices, hotel locations, the map of traveled places, etc. Now, this information is available in this system and it can be used to decide a better plan traveler. Decision support systems are the type of information systems expressly developed to support the decision making process and to assist a decision maker. So, this system is implemented as the decision support system for travelling. Moreover, this system describes the use of intelligent agents for extracting and integrating data to improve the ability to plan a travel. These agents can extract data, integrate this data to support travel planning and monitor all aspects of a trip. Therefore, a traveler decision support system by using intelligent agents will develop to support travelers in making their decision on a suitable track when they are faced with a number of alternative track options.

A Multi-Agent Decision Support Architecture for Knowledge Representation and Exchange

2011 ◽  
pp. 2558-2574
Author(s):  
Rahul Singh
Keyword(s):  
Decision Support ◽  
Knowledge Representation ◽  
Intelligent Agents ◽  
Machine Learning Techniques ◽  
Specific Knowledge ◽  
Knowledge Based ◽  
Intelligent Software Agents ◽  
Learning Techniques ◽  
Domain Specific Knowledge ◽  
Multi Agent

Organizations rely on knowledge-driven systems for delivering problem-specific knowledge over Internet-based distributed platforms to decision-makers. Recent advances in systems support for problem solving have seen increased use of artificial intelligence (AI) techniques for knowledge representation in multiple forms. This article presents an Intelligent Knowledge-based Multi-agent Decision Support Architecture” (IKMDSA) to illustrate how to represent and exchange domain-specific knowledge in XMLformat through intelligent agents to create, exchange and use knowledge in decision support. IKMDSA integrates knowledge discovery and machine learning techniques for the creation of knowledge from organizational data; and knowledge repositories (KR) for its storage management and use by intelligent software agents in providing effective knowledge-driven decision support. Implementation details of the architecture, its business implications and directions for further research are discussed.

GIS as Spatial Decision Support Systems

2011 ◽  
pp. 151-174 ◽  
Author(s):  
Suprasith Jarupathirun ◽  
Fatemeh Zahedi
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Intelligent Agents ◽  
Support Systems ◽  
Decision Aids ◽  
Geographic Information ◽  
Spatial Decision Support ◽  
Spatial Decision Support Systems ◽  
Decision Tools ◽  
Spatial Dimensions

This chapter discusses the use of geographic information systems (GIS) for spatial decision support systems (SDSS). It argues that the increased availability in spatial business data has created new opportunities for the use of GIS in creating decision tools for use in a variety of decisions that involve spatial dimensions. This chapter identifies visualization and analytical capabilities of GIS that make such systems uniquely appropriate as decision aids, and presents a conceptual model for measuring the efficacy of GIS-based SDSS. The discussions on the applications of SDSS and future enhancements using intelligent agents are intended to inform practitioners and researchers of the opportunities for the enhancement and use of such systems.

HYBRID TECHNOLOGY FOR SELF-ORGANIZATION OF RESOURCES OF PERVASIVE ENVIRONMENT FOR OPERATIONAL DECISION SUPPORT

2010 ◽  
Vol 19 (02) ◽  
pp. 211-229 ◽  
Author(s):  
ALEXANDER SMIRNOV ◽  
TATIANA LEVASHOVA ◽  
NIKOLAY SHILOV ◽  
ALEXEY KASHEVNIK
Keyword(s):  
Decision Support ◽  
Web Services ◽  
Decision Support System ◽  
Support System ◽  
Intelligent Agents ◽  
Technology Implementation ◽  
Technology Application ◽  
Hybrid Technology ◽  
Collaborative Environment ◽  
Pervasive Environment

The paper addresses the development of a hybrid technology for operational decision support in a pervasive environment. The technology encompasses the idea of implementing a decision support system as a set of Web-services. The Web-services are intended to form an ad-hoc collaborative environment, whose members cooperate with an objective of serving the current needs according to the decision situation. The collaborative environment is made up of resources of a pervasive environment. The technology is focused on three types of resources to be organized: information, problem-solving, and acting, and is supported by a service-based architecture of the decision support system providing types of Web-services needed for this technology implementation. The hybrid technology integrates technologies of ontology management, context management, constraint satisfaction, Web-services, profiling, and intelligent agents. The technology application is illustrated by the decision support for dynamic logistics.

Sign in / Sign up

Export Citation Format

Share Document