scholarly journals ENABLING INTELLIGENT AGENTS AND THE SEMANTIC WEB FOR E-COMMERCE

2014 ◽  
pp. 153-159
Author(s):  
Yefim H. Kats
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Intelligent Agent ◽  
Intelligent Software

This paper examines an impact of the growing intelligent agent technologies and the Semantic Web on the phenomenon of e-commerce. We discuss the problems – technical as well as legal – arising from the emergence of the new forms of intelligent software and consider the possible solutions. In particular, we review how the integration of the Semantic Web and intelligent agents can provide a new environment for the secure and scalable e-commerce applications.

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.

A DYNAMIC INFERENCE MODEL FOR INTELLIGENT AGENTS

2001 ◽  
Vol 11 (05) ◽  
pp. 509-528 ◽  
Author(s):  
CHUNYAN MIAO ◽  
ANGELA GOH ◽  
YUAN MIAO ◽  
ZHONGHUA YANG
Keyword(s):  
Intelligent Agents ◽  
Intelligent Agent ◽  
Human Beings ◽  
Inference Model ◽  
Intelligent Software ◽  
Temporal Concepts ◽  
Intelligent Software Agents ◽  
New Type ◽  
Causal Impact ◽  
Impact Models

This paper proposes an Agent Inference Model (AIM) for constructing intelligent software agents. AIM has the ability of representing various types of fuzzy concepts, temporal concepts, and dynamic causal relationships between concepts. It also has the ability of handling feedback and analyzing inference patterns over different causal impact models. Based on AIM, a new type of intelligent agent, Dynamic Inference Agent (DIA) is presented. A dynamic inference agent has the ability to model, infer and make decisions on behalf of human beings. It uses numeric representations and computation instead of symbolic representation and logic deduction to represent knowledge and to carry out the inferences respectively. Thus the construction of DIA is simplified and the implementation code is compact. The application of DIA to various areas, especially for electronic commerce over the Internet is exemplified.

Semantics and Agents Oriented Web Personalization

2015 ◽  
Vol 6 (2) ◽  
pp. 35-49 ◽  
Author(s):  
Aarti Singh ◽  
Anu Sharma ◽  
Nilanjan Dey
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Web Mining ◽  
Information Overload ◽  
Software Agents ◽  
User Profile ◽  
Content Management ◽  
Multi Agent Systems ◽  
Web Personalization ◽  
Intelligent Software

Advent of technologies like semantic web, multi-agent systems, web mining has changed the internet as knowledge provider. Web personalization offers a solution to the information overload problem in current web by providing users a personalized experience, considering their interest, behavior, context and emotions. Semantic web technology is based on use of software agents, ontologies and reasoning to add meaning to web information. An important technology for achieving personalization is the use of independent intelligent software agents. This work reviews, web personalization in the light of semantic web and software agent technology. A comparative study of recent works in the domain of web personalization has been carried out for this purpose. This review highlights ample scope for application of intelligent agents in the web personalization domain for solving many existing issues like personalized content management, user profile learning, modeling and adaptive interactions with users.

scholarly journals USE OF INTELLEGENT AND BLOCK CHAIN TECHNOLOGIES IN INFORMATION MANAGEMENT Minsk Innovation University

2018 ◽  
pp. 45-50 ◽  
Author(s):  
U. A. Vishniakou
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Information Management ◽  
Intelligent Agents ◽  
Intelligent System ◽  
Semantic Network ◽  
The Internet ◽  
Semantic Level ◽  
Intelligent Software ◽  
Block Chain

The aim of this work is the analysis of methods, approaches, technologies, means of information management (IM), using both conventional technologies and adding new intellectual and block chain. Trends in the use of intelligent technologies in information management are given. The developments in the field of intelligent agents based on semantic web, web-services and semantic web-services, the use of cloud computing (CC) are shown. The main ideas of semantic technologies, in which a page of the semantic network contains information in two languages: the natural and special, understood only by intelligent software agents (IA) are discussed.The use of block chain technology for the control of various material and non-material assets are done. Technically, the block chain technology is another application layer on top of the stack of the Internet protocols and can be integrated with the semantic level. The use of intelligent technologies in the information management in the cloud area with the work of IA. The intelligent web (web 3.0), which became the next stage in the development of the Internet is discussed. It forms the semantics on the ontology dase, creating new opportunities for IA to perform various user requests. Analyzes the major developments in the field of intellectualization of IM, and the main tendencies of their development. The result was a list of criteria and their values, which must meet an intelligent system for IM.As trends in the development of IM is considered the improvement of models and methods of joint activity of IA in the cloud area using block chain technology. Three directions of development of intellectual control system are proposed. As the development of information management proposed the creation of an instrumental platform based on multi agent approach, integrating semantic and block chain technology in the cloud area.

Ontologies and Intelligent Agents

2010 ◽  
pp. 49-73
Author(s):  
Kostas Kolomvatsos
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Intelligent Agent ◽  
Basic Element

The emerged form of information with computer-processable meaning (semantics) as presented in the framework of the Semantic Web (SW) facilitates machines to access it more efficiently. Information is semantically annotated in order to ease the discovery and retrieval of knowledge. Ontologies are the basic element of the SW. They carry knowledge about a domain and enable interoperability between different resources. Another technology that draws considerable attention nowadays is the technology of Intelligent Agents. Intelligent agents act on behalf of a user to complete tasks and may adapt their behavior to achieve their objectives. The objective of this chapter is to provide an exhaustive description of fundamentals regarding the combination of SW and intelligent agent technologies.

An ontology, intelligent agent-based framework for the provision of semantic web services

2009 ◽  
Vol 36 (2) ◽  
pp. 3167-3187 ◽  
Author(s):  
Francisco García-Sánchez ◽  
Rafael Valencia-García ◽  
Rodrigo Martínez-Béjar ◽  
Jesualdo T. Fernández-Breis
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Intelligent Agent ◽  
Semantic Web Services ◽  
Agent Based

scholarly journals Intelligence via ultrafilters: structural properties of some intelligence comparators of deterministic Legg-Hutter agents

2019 ◽  
Vol 10 (1) ◽  
pp. 24-45
Author(s):  
Samuel Allen Alexander
Keyword(s):  
Structural Properties ◽  
Intelligent Agents ◽  
Intelligent Agent ◽  
Related Question ◽  
Practical Intelligence ◽  
Guiding Principle ◽  
Intelligence Measures ◽  
Open Question ◽  
Structural Theorems

Abstract Legg and Hutter, as well as subsequent authors, considered intelligent agents through the lens of interaction with reward-giving environments, attempting to assign numeric intelligence measures to such agents, with the guiding principle that a more intelligent agent should gain higher rewards from environments in some aggregate sense. In this paper, we consider a related question: rather than measure numeric intelligence of one Legg-Hutter agent, how can we compare the relative intelligence of two Legg-Hutter agents? We propose an elegant answer based on the following insight: we can view Legg-Hutter agents as candidates in an election, whose voters are environments, letting each environment vote (via its rewards) which agent (if either) is more intelligent. This leads to an abstract family of comparators simple enough that we can prove some structural theorems about them. It is an open question whether these structural theorems apply to more practical intelligence measures.

scholarly journals An intelligent agent model for learning group development in the digital learning environment: A systematic literature review

2020 ◽  
Vol 9 (3) ◽  
pp. 1159-1166
Author(s):  
Budi Laksono Putro ◽  
Yusep Rosmansyah ◽  
Suhardi Suhardi
Keyword(s):  
Literature Review ◽  
Learning Environment ◽  
Systematic Literature Review ◽  
Intelligent Agents ◽  
Intelligent Agent ◽  
Group Development ◽  
Collaborative Problem Solving ◽  
Digital Learning ◽  
Agent Model ◽  
Digital Learning Environment

Group development is the first and most important step for the success of collaborative problem solving (CPS) learning in the digital learning environment (DLE). A literacy study is needed for studies in the intelligent agent domain for group development of collaborative learning in DLE. This paper is a systematic literature review (SLR) of intelligent agents for group formation from 2001 to 2019. This paper aims to find answers to 4 (four) research questions, namely: 1) What components to develop intelligent agents for group development; 2) What is the intelligent agent model for group development; 3) How are the metrics for measuring intelligent agent performance; and 4) How is the Framework for developing intelligent agent. The components of the intelligent agent model consist of: member attributes, group attributes (group constraints), and intelligent techniques. This research refers to Srba and Bielikova's group development model. The stages of the model are formation, performing and closing. An intelligent agent model at the formation stage. A performance metric for the intelligent agent at the performance stage. The framework for developing an intelligent agent is a reference to the stages of development, component selection techniques, and performance measurement of an intelligent agent.

Intelligent Agents and Autonomous Robots

2019 ◽  
pp. 1134-1143
Author(s):  
Deepshikha Bhargava
Keyword(s):  
Language Processing ◽  
Intelligent Agents ◽  
Driving Force ◽  
Autonomous Agents ◽  
New Technologies ◽  
Autonomous Robots ◽  
Software Agents ◽  
Intelligent Agent ◽  
Intelligent Robots ◽  
Systems Software

Over decades new technologies, algorithms and methods are evolved and proposed. We can witness a paradigm shift from typewriters to computers, mechanics to mechnotronics, physics to aerodynamics, chemistry to computational chemistry and so on. Such advancements are the result of continuing research; which is still a driving force of researchers. In the same way, the research in the field of artificial intelligence (Russell, Stuart & Norvig, 2003) is major thrust area of researchers. Research in AI have coined different concepts like natural language processing, expert systems, software agents, learning, knowledge management, robotics to name a few. The objective of this chapter is to highlight the research path from software agents to robotics. This chapter begins with the introduction of software agents. The chapter further progresses with the discussion on intelligent agent, autonomous agents, autonomous robots, intelligent robots in different sections. The chapter finally concluded with the fine line between intelligent agents and autonomous robots.

Enabling Technologies for the Semantic Web

2005 ◽  
pp. 39-56
Author(s):  
Kevin R. Parker
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Extensible Markup Language ◽  
Markup Language ◽  
Enabling Technologies ◽  
Key Technologies ◽  
Extensible Markup ◽  
Broad Overview

Before understanding the Semantic Web and its associated benefits, one must first be somewhat familiar with the enabling technologies upon which the Semantic Web is based. The extensible markup language (XML), uniform resource identifiers (URIs), resource definition framework (RDF), ontologies, and intelligent agents are all key tithe realization of the Semantic Web. Understanding these key technologies gives readers a firm foundation before progressing to subsequent chapters. This chapter provides a broad overview of each technology, and readers new to these technologies are provided with references to more detailed explanations.

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