Book Review: E-learning with Intelligent Agents [review of "Designing Distributed Learning Environments with Intelligent Software Agents" (Lin, F.O., ed.; 2004)]

2008 ◽  
Vol 9 (2) ◽  
pp. 4-4 ◽  
Author(s):  
Maria Ganzha
Keyword(s):  
Learning Environments ◽  
Intelligent Agents ◽  
Software Agents ◽  
Distributed Learning ◽  
Intelligent Software ◽  
Distributed Learning Environments ◽  
Intelligent Software Agents ◽  
E Learning

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.

scholarly journals Intelligent agents, Internet information and interface

1995 ◽  
Vol 11 (2) ◽  
Author(s):  
James Meek
Keyword(s):  
Intelligent Agents ◽  
Software Agents ◽  
Intelligent Software ◽  
Intelligent Software Agents ◽  
Internet Information

<span>A review of intelligent software agents and their relevance to networked information touching on some of their emerging potential and on interface considerations.</span>

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

Affective Agents in E-Learning Platforms

2012 ◽  
pp. 1225-1233
Author(s):  
Christos N. Moridis ◽  
Anastasios A. Economides
Keyword(s):  
Artificial Intelligence ◽  
Learning Environments ◽  
Intelligent Agents ◽  
Intelligent Agent ◽  
Human Learning ◽  
Human Reasoning ◽  
Conversational Agents ◽  
Emotional Aspects ◽  
E Learning ◽  
Learning Platforms

During recent decades there has been an extensive progress towards several Artificial Intelligence (AI) concepts, such as that of intelligent agent. Meanwhile, it has been established that emotions play a crucial role concerning human reasoning and learning. Thus, developing an intelligent agent able to recognize and express emotions has been considered an enormous challenge for AI researchers. Embedding a computational model of emotions in intelligent agents can be beneficial in a variety of domains, including e-learning applications. However, until recently emotional aspects of human learning were not taken into account when designing e-learning platforms. Various issues arise when considering the development of affective agents in e-learning environments, such as issues relating to agents’ appearance, as well as ways for those agents to recognize learners’ emotions and express emotional support. Embodied conversational agents (ECAs) with empathetic behaviour have been suggested to be one effective way for those agents to provide emotional feedback to learners’ emotions. There has been some valuable research towards this direction, but a lot of work still needs to be done to advance scientific knowledge.

Intelligent Agents for E-Learning

2011 ◽  
pp. 25-42
Author(s):  
Ralf Bruns ◽  
Jürgen Dunkel
Keyword(s):  
Web Sites ◽  
Intelligent Agents ◽  
Domain Knowledge ◽  
Multi Agent Systems ◽  
Semantic Web Technologies ◽  
Private Data ◽  
Intelligent Software Agents ◽  
E Learning ◽  
The One ◽  
New Generation

We propose the software architecture of a new generation of advisory systems using Intelligent Agent and Semantic Web technologies. Multi-agent systems provide a well-suited paradigm to implement negotiation processes in consultancy situations. Intelligent software agents act as clients and advisors using their knowledge in order to assist human users. In the proposed architecture the domain knowledge is semantically modeled by means of XML-based ontology languages such as OWL. Using an inference engine the agents reason on base of their knowledge to make decisions or proposals. The agent knowledge consists of different types of data: on the one hand private data, which has to be protected against unauthorized access, and on the other hand publicly accessible data spread over different web sites. Comparable to a real consultancy situation, an agent only reveals sensitive private data if it is indispensable for finding a solution. In addition, depending on the actual consultancy situation each agent dynamically expands its knowledge base by accessing OWL knowledge sources from the Internet. The usefulness of our approach is proved by the implementation of an advisory system whose objective is to develop virtual student advisers that render support to university students in order to successfully organize und perform their studies.

Interface Design

2011 ◽  
pp. 157-172
Author(s):  
Badrul Khan
Keyword(s):  
Blended Learning ◽  
Learning Environments ◽  
Interface Design ◽  
Distributed Learning ◽  
Critical Dimensions ◽  
Learning Modules ◽  
E Learning ◽  
Learning Factors ◽  
Resource Support ◽  
Review Criteria

The purpose of the E-Learning Quick Checklist book is to walk you through the various factors (encompassing these eight dimensions) important to developing, evaluating, and implementing open, flexible and distributed learning environments. This book is designed as a Quick Checklist for e-learning. It contains many practical items that you can use as review criteria to check if e-learning modules, courses and programs provide the level of services that learners (or consumers) should expect. Items in the checklist encompass the critical dimensions of an e-learning environment, including pedagogical, technological, interface design, evaluation, management, resource support, ethical, and institutional. Throughout this book, various critical e-learning and blended-learning factors are presented as questions or items that you can ask yourself when planning, designing, evaluating, and implementing e-learning and/or blended-learning modules, courses, and programs.

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