Intelligent Software Agents in E-Commerce

2011 ◽  
pp. 549-554
Author(s):  
Mahesh S. Raisinghani ◽  
Christopher Klassen ◽  
Lawrence L. Schkade

Agent technology is one of the most widely discussed topics in information systems and computer science literature. New software products are being introduced each day. A growing number of computer information professionals recognize that there are definite issues surrounding intelligent agent terminology. These must be resolved if agent technology is to continue to develop and establish.

Author(s):  
Mahesh S. Raisinghani ◽  
Cristpoher Klassen ◽  
Lawrence L. Schkade

Agent technology is one of the most widely discussed topics in information systems and computer science literature. New software products are being introduced each day. A growing number of computer information professionals recognize that there are definite issues surrounding intelligent agent terminology. These must be resolved if agent technology is to continue to develop and establish.


Author(s):  
Mahesh S. Raisinghani ◽  
Christopher Klassen ◽  
Lawrence L. Schkade

Agent technology is one of the most widely discussed topics in information systems and computer science literature. New software products are being introduced each day. A growing number of computer information professionals recognize that there are definite issues surrounding intelligent agent terminology. These must be resolved if agent technology is to continue to develop and establish. Current research on intelligent agent software technology can be categorized as two main areas: technological and social. In the excitement of emergent technology, people often forget to scrutinize how new technology may impact their lives. The social dimension of technological progress is the driving force and most central concern of technology. Technology is not created for its own sake as a technological imperative. This article critiques the current state of software intelligent agents by examining technological issues and the social implications of intelligent agent software technology.


Author(s):  
Mahesh S. Raisinghani

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.


2011 ◽  
pp. 104-112 ◽  
Author(s):  
Mahesh S. Raisinghani ◽  
Christopher Klassen ◽  
Lawrence L. Schkade

Although there is no firm consensus on what constitutes an intelligent agent (or software agent), an intelligent agent, when a new task is delegated by the user, should determine precisely what its goal is, evaluate how the goal can be reached in an effective manner, and perform the necessary actions by learning from past experience and responding to unforeseen situations with its adaptive, self-starting, and temporal continuous reasoning strategies. It needs to be not only cooperative and mobile in order to perform its tasks by interacting with other agents but also reactive and autonomous to sense the status quo and act independently to make progress towards its goals (Baek et al., 1999; Wang, 1999). Software agents are goal-directed and possess abilities such as autonomy, collaborative behavior, and inferential capability. Intelligent agents can take different forms, but an intelligent agent can initiate and make decisions without human intervention and have the capability to infer appropriate high-level goals from user actions and requests and take actions to achieve these goals (Huang, 1999; Nardi et al., 1998; Wang, 1999). The intelligent software agent is a computational entity than can adapt to the environment, making it capable of interacting with other agents and transporting itself across different systems in a network.


2018 ◽  
Vol 28 (4) ◽  
pp. 735-774 ◽  
Author(s):  
Christopher Burr ◽  
Nello Cristianini ◽  
James Ladyman

2009 ◽  
pp. 1452-1457
Author(s):  
Xin Luo ◽  
Somasheker Akkaladevi

Cowan et al. (2002) argued that the human cognitive ability to search for information and to evaluate their usefulness is extremely limited in comparison to those of computers. In detail, it’s cumbersome and time-consuming for a person to search for information from limited resources and to evaluate the information’s usefulness. They further indicated that while people are able to perform several queries in parallel and are good at drawing parallels and analogies between pieces of information, advanced systems that embody ISA architecture are far more effective in terms of calculation power and parallel processing abilities, particularly in the quantities of material they can process (Cowan et al. 2002). According to Bradshaw (1997), information complexity will continue to increase dramatically in the coming decades. He further contended that the dynamic and distributed nature of both data and applications require that software not merely respond to requests for information but intelligently anticipate, adapt, and actively seek ways to support users.


2009 ◽  
pp. 283-302
Author(s):  
Dickson K.W. Chiu ◽  
S.C. Cheun ◽  
Ho-Fung Leung

In a service-oriented enterprise, the professional workforce such as salespersons and support staff tends to be mobile with the recent advances in mobile technologies. There are increasing demands for the support of mobile workforce management (MWM) across multiple platforms in order to integrate the disparate business functions of the mobile professional workforce and management with a unified infrastructure, together with the provision of personalized assistance and automation. Typically, MWM involves tight collaboration, negotiation, and sophisticated business-domain knowledge, and thus can be facilitated with the use of intelligent software agents. As mobile devices become more powerful, intelligent software agents can now be deployed on these devices and hence are also subject to mobility. Therefore, a multiagent information-system (MAIS) infrastructure provides a suitable paradigm to capture the concepts and requirements of an MWM as well as a phased development and deployment. In this book chapter, we illustrate our approach with a case study at a large telecommunication enterprise. We show how to formulate a scalable, flexible, and intelligent MAIS with agent clusters. Each agent cluster comprises several types of agents to achieve the goal of each phase of the workforce-management process, namely, task formulation, matchmaking, brokering, commuting, and service.


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