scholarly journals An Analysis of the Interaction Between Intelligent Software Agents and Human Users

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

SMART Buildings: Intelligent Software Agents

2009 ◽  
pp. 9-17 ◽  
Author(s):  
Wim Zeiler ◽  
Rinus van Houten ◽  
Gert Boxem
Keyword(s):  
Software Agents ◽  
Smart Buildings ◽  
Intelligent Software ◽  
Intelligent Software Agents

Intelligent Software Agents Analysis in E-Commerce II

2009 ◽  
pp. 1452-1457
Author(s):  
Xin Luo ◽  
Somasheker Akkaladevi
Keyword(s):  
Parallel Processing ◽  
Cognitive Ability ◽  
Software Agents ◽  
Limited Resources ◽  
Information Complexity ◽  
Intelligent Software ◽  
Intelligent Software Agents ◽  
Processing Abilities ◽  
Search For Information

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.

Mobile Workforce Management in a Service-Oriented Enterprise

2009 ◽  
pp. 283-302
Author(s):  
Dickson K.W. Chiu ◽  
S.C. Cheun ◽  
Ho-Fung Leung
Keyword(s):  
Domain Knowledge ◽  
Software Agents ◽  
Mobile Technologies ◽  
Workforce Management ◽  
Intelligent Software ◽  
Intelligent Software Agents ◽  
Service Oriented ◽  
Business Functions ◽  
Telecommunication Enterprise ◽  
Phased Development

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.

Intelligent Software Agents in Electronic Commerce

2011 ◽  
pp. 104-112 ◽  
Author(s):  
Mahesh S. Raisinghani ◽  
Christopher Klassen ◽  
Lawrence L. Schkade
Keyword(s):  
Intelligent Agents ◽  
Software Agents ◽  
Intelligent Agent ◽  
Software Agent ◽  
Reasoning Strategies ◽  
Intelligent Software ◽  
Collaborative Behavior ◽  
Intelligent Software Agents ◽  
The Status ◽  
High Level

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.

Intelligent Software Agents

2011 ◽  
pp. 155-172
Author(s):  
Stefan Kirn ◽  
Mathias Petsch ◽  
Brian Lees
Keyword(s):  
Intelligent Agents ◽  
New Technology ◽  
Software Agents ◽  
Security Architecture ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Security Issues ◽  
Intelligent Software ◽  
Intelligent Software Agents ◽  
Multi Agent

For a new technology, such as that offered by intelligent agents, to be successful and widely accepted, it is necessary for systems, based on that technology, to be capable of maintaining security and consistency of operation when integrated into the existing infrastructure of an organisation. This paper explores some of the security issues relating to application of intelligent agents and the integration of such systems into existing organisations. First, existing information security issues for enterprises are considered. Then, a short introduction to the new technology of agents and agent systems is given. Following this, the special security problems of the new technology of software agents and the emerging risks for software and enterprises are discussed. Finally, a new security architecture for multi-agent systems is proposed, together with an explanation of how this multilevel architecture can help to improve the security of agent systems.

An Intelligent, Multi-Agent Environment for Concurrent and Collaborative Configuration of Personal Computers

2002 ◽  
Vol 10 (2) ◽  
pp. 143-151 ◽  
Author(s):  
Y.C. Ng ◽  
K.S. Tey ◽  
K.R. Subramanian ◽  
S.B. Tor ◽  
L.P. Khoo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
System Architecture ◽  
Software Agents ◽  
Disk Drive ◽  
Collaborative Engineering ◽  
Intelligent Software ◽  
Intelligent Software Agents ◽  
Multi Agent ◽  
And Performance ◽  
Implementation Problems

Although Concurrent and Collaborative Engineering (CCE) has enjoyed widespread acceptance in industry, many implementation problems remain. With the advent of more powerful artificial intelligence techniques, CCE can be further improved. This paper demonstrates how intelligent software agents may be deployed to facilitate concurrent, collaborative engineering. A system architecture, Java Agent Alive!, is presented as a multi-agent environment. A case study of configuring a personal computer (PC) from its processor, memory and hard disk drive is discussed to highlight the power of software agents in negotiating for the PC configuration with the best price and performance. A software agent is created and assigned to each of the PC components. These agents attend two levels of agent conferences, viz. the bidding conference and the PC component vendor's conference. At both conferences, each agent strives to offer components with the best performance and the lowest price. The agents were ascribed artificial intelligence through the Java Expert System Shell (JESS). At the end of the negotiations, five PC configurations were finalised that met the expectations of the user, who is informed of the outcome via e-mail. The strengths and limitations of the system architecture and the domain application of PC assembly, as well as means to enhance security, are also discussed. Some recommendations to further improve the limitations of Java Agent Alive! and the PC Assembly application are made.

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