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.

Intelligent Multi-Agent Systems

2009 ◽  
pp. 464-469
Author(s):  
Uros Krcadinac ◽  
Milan Stankovic ◽  
Vitomir Kovanovic ◽  
Jelena Jovanovic
Keyword(s):  
Autonomous Agents ◽  
Research Community ◽  
Object Oriented Programming ◽  
Multi Agent Systems ◽  
Autonomous Action ◽  
Agent Systems ◽  
Intelligent Software ◽  
Intelligent Software Agents ◽  
Object Based ◽  
Multi Agent

Since the AAAI (http://www.aaai.org) Spring Symposium in 1994, intelligent software agents and agentbased systems became one of the most significant and exciting areas of research and development (R&D) that inspired many scientific and commercial projects. In a nutshell, an agent is a computer program that is capable of performing a flexible, autonomous action in typically dynamic and unpredictable domains (Luck, McBurney, Shehory, & Willmott, 2005). Agents emerged as a response of the IT research community to the new data-processing requirements that traditional computing models and paradigms were increasingly incapable to deal with (e.g., the huge and ever-increasing quantities of available data). Agent-oriented R&D has its roots in different disciplines. Undoubtedly, the main contribution to the field of autonomous agents came from artificial intelligence (AI) which is focused on building intelligent artifacts; and if these artifacts sense and act in some environment, then they can be considered agents (Russell & Norvig, 1995). Also, object-oriented programming (Booch, 2004), concurrent object-based systems (Agha, Wegner, & Yonezawa, 1993), and human-computer interaction (Maes, 1994) are fields that have constantly driven forward the agent R&D in the last few decades.

Intelligent Software Agents with Applications in Focus

2011 ◽  
pp. 950-955
Author(s):  
Mario Jankovic-Romano ◽  
Milan Stankovic ◽  
Uroš Krcadinac
Keyword(s):  
Traffic Control ◽  
Software Agents ◽  
Real Life ◽  
Object Oriented Programming ◽  
Mobile Systems ◽  
Multi Agent Systems ◽  
Information Recovery ◽  
Intelligent Software ◽  
Intelligent Software Agents ◽  
Multi Agent

Most people are familiar with the concept of agents in real life. There are stock-market agents, sports agents, real-estate agents, etc. Agents are used to filter and present information to consumers. Likewise, during the last couple of decades, people have developed software agents, that have the similar role. They behave intelligently, run on computers, and are autonomous, but are not human beings. Basically, an agent is a computer program that is capable of performing a flexible and independent action in typically dynamic and unpredictable domains (Luck, McBurney, Shehory, & Willmott, 2005). Agents are capable of performing actions and making decisions without the guidance of a human. Software agents emerged in the IT because of the ever-growing need for information processing, and the problems concerning dealing and working with large quantities of data. Especially important is how agents act with other agents in the same environment, and the connections they form to find, refine and present the information in a best way. Agents certainly can do tasks better if they perform together, and that is why the multi-agent systems were developed. The concept of an agent has become important in a diverse range of sub-disciplines of IT, including software engineering, networking, mobile systems, control systems, decision support, information recovery and management, e-commerce, and many others. Agents are now used in an increasingly wide number of applications — ranging from comparatively small systems such as web or e-mail filters to large, complex systems such as air-traffic control, that have a large dependency on fast and precise decision making. Undoubtedly, the main contribution to the field of intelligent software agents came from the field of artificial intelligence (AI). The main focus of AI is to build intelligent entities and if these entities sense and act in some environment, then they can be considered agents (Russell & Norvig, 1995). Also, object-oriented programming (Booch, 2004), concurrent object-based systems (Agha, Wegner, and Yonezawa, 1993), and human- computer interaction (Maes, 1994) are fields that constantly drive forward the development of agents.

scholarly journals Agents’ ontologies negotiation in cohesive hybrid intelligent multi-agent systems

2021 ◽  
Vol 2094 (3) ◽  
pp. 032033
Author(s):  
I A Kirikov ◽  
S V Listopad ◽  
A S Luchko
Keyword(s):  
Intelligent Agents ◽  
Intelligent Systems ◽  
Multi Agent Systems ◽  
Labor Costs ◽  
Joint Work ◽  
Working Process ◽  
Agent Systems ◽  
Development Teams ◽  
Multi Agent ◽  
Domain Models

Abstract The paper proposes the model for negotiating intelligent agents’ ontologies in cohesive hybrid intelligent multi-agent systems. Intelligent agent in this study will be called relatively autonomous software entity with developed domain models and goal-setting mechanisms. When such agents have to work together within single hybrid intelligent multi-agent systems to solve some problem, the working process “go wild”, if there are significant differences between the agents’ “points of view” on the domain, goals and rules of joint work. In this regard, in order to reduce labor costs for integrating intelligent agents into a single system, the concept of cohesive hybrid intelligent multi-agent systems was proposed that implement mechanisms for negotiating goals, domain models and building a protocol for solving the problems posed. The presence of these mechanisms is especially important when building intelligent systems from intelligent agents created by various independent development teams.

Software Agents in Today's Digital Economy

2001 ◽  
pp. 88-100 ◽  
Author(s):  
Mahesh S. Raisinghani
Keyword(s):  
Intelligent Agents ◽  
New Technology ◽  
Software Agents ◽  
Information Filtering ◽  
Intelligent Agent ◽  
Social Dimension ◽  
Economic Changes ◽  
Software Products ◽  
Intelligent Software Agents ◽  
High Level

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.

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.

scholarly journals Reports on the 2018 AAAI Spring Symposium Series

AI Magazine ◽  
2018 ◽  
Vol 39 (4) ◽  
pp. 29-35
Author(s):  
Christopher Amato ◽  
Haitham Bou Ammar ◽  
Elizabeth Churchill ◽  
Erez Karpas ◽  
Takashi Kido ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Agents ◽  
Well Being ◽  
Machine Intelligence ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Internet Of Everything ◽  
Symposium Series ◽  
Multi Agent ◽  
And Control

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University’s Department of Computer Science, presented the 2018 Spring Symposium Series, held Monday through Wednesday, March 26–28, 2018, on the campus of Stanford University. The seven symposia held were AI and Society: Ethics, Safety and Trustworthiness in Intelligent Agents; Artificial Intelligence for the Internet of Everything; Beyond Machine Intelligence: Understanding Cognitive Bias and Humanity for Well-Being AI; Data Efficient Reinforcement Learning; The Design of the User Experience for Artificial Intelligence (the UX of AI); Integrated Representation, Reasoning, and Learning in Robotics; Learning, Inference, and Control of Multi-Agent Systems. This report, compiled from organizers of the symposia, summarizes the research of five of the symposia that took place.

scholarly journals Special issue on logics for intelligent agents and multi-agent systems

2011 ◽  
Vol 9 (4) ◽  
pp. 221-222 ◽  
Author(s):  
Mehmet A. Orgun ◽  
Guido Governatori ◽  
Chuchang Liu ◽  
Mark Reynolds ◽  
Abdul Sattar
Keyword(s):  
Intelligent Agents ◽  
Multi Agent Systems ◽  
Special Issue ◽  
Agent Systems ◽  
Multi Agent

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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