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Software Agents in Today's Digital Economy: Transition to the Knowledge Society

Software Agents in Today's Digital Economy: Transition to the Knowledge Society
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Author(s): Mahesh S. Raisinghani (University of Dallas, USA)
Copyright: 2001
Pages: 13
Source title: Internet Commerce and Software Agents: Cases, Technologies and Opportunities
Source Author(s)/Editor(s): Syed Mahbubhur Rahman (Minnesota State University, Mankato, USA) and Robert J. Bignall (Monash University, Australia)
DOI: 10.4018/978-1-930708-01-3.ch006

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Abstract

One of the most discussed topics in the information systems literature today is software agent/intelligent agent technology. Software agents are high-level software abstractions with inherent capabilities for communication, decision making, control, and autonomy. They are programs that perform functions such as information gathering, information filtering, or mediation (running in the background) on behalf of a person or entity. They have several aliases such as agents, bots, chatterbots, databots, intellibots, and intelligent software agents/robots. They provide a powerful mechanism to address complex software engineering problems such as abstraction, encapsulation, modularity, reusability, concurrency, and distributed operations. Much research has been devoted to this topic, and more and more new software products billed as having intelligent agent functionality are being introduced on the market every day. The research that is being done, however, does not wholeheartedly endorse this trend. The current research into intelligent agent software technology can be divided into two main areas: technological and social. The latter area is particularly important since, in the excitement of new and emergent technology, people often forget to examine what impact the new technology will have on people’s lives. In fact, the social dimension of all technology is the driving force and most important consideration of technology itself. This chapter presents a socio-technical perspective on intelligent agents and proposes a framework based on the data lifecycle and knowledge discovery using intelligent agents. One of the key ideas of this chapter is best stated by Peter F. Drucker in Management Challenges for the 21st Century when he suggests that in this period of profound social and economic changes, managers should focus on the meaning of information, not the technology that collects it.

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