Application Of Intelligent Agents Research Articles

A Systematic Review of Exploring the Potential of Teachable Agents in English Learning

Language learning has dramatically influenced the extensiveness of web-based learning, AI applications, smart content, personalized tutoring systems, virtual facilitators. This paper aims to review the empirical evidence on the application of intelligent agents in English learning to define the future research perspectives of Teachable Agents-assisted English education. After a systematic online data search, the investigator analyzed nine empirical studies on how Teachable agents have potential English teaching and learning benefits. The results indicate that (1) most studies conducted with large sample size at university level followed by elementary level, (2) instructional design were in dialogue and image form, (3) emerged two categories- Interaction and integration, (4) most of them used experimental research in different settings. This study suggests that TAs substantially play a supportive role, enhance their involvement, scaffold their learning, and become self-regulated learners. Hence, we prospect the need for a future-oriented vision regarding AI and intelligent technologies- assisted language learning for non-native speakers.

Intelligent agent-assisted organizational memory in knowledge management systems

Purpose The purpose of this paper is to examine the application of intelligent agents (IAs) in organizational memory systems within the larger schema of knowledge management (KM) strategies. This includes targeted roles of IAs in relation to institutional memory approaches. Design/methodology/approach A conceptual exploration of related sections of the Grundspenkis seven-layer intelligent enterprise memory framework that serves to identify, retain, deliver and reuse information for future utilization is conducted. Applications of IAs in multiple industries are presented to illustrate the conceptual model in practice. Findings This paper identifies arising roles that IAs perform in information search, retrieval and analysis in the organizational memory formation process and extensions that have emerged in a non-linear bi-directional form. These layered roles include obtaining and reapplying important information as part of extended human–machine cognition. Research limitations/implications While exploratory and conceptual in nature, this research paper discusses IAs as possible components in the advancement of organization memory. Practical implications By analyzing the application of IAs in different industries, across select layers of a KM structure, groundwork is laid for both descriptive research (i.e. where and how artificial intelligence is being used in those industries) and prescriptive practice (i.e. how other industries can benefit from such assistance and what patterns of implementation to expect). Originality/value This study explores the role IAs play in helping knowledge workers gather, retain and find relevant information and how KM strategies may assist organizational memory.

Application of Intelligent Multi Agent Based Systems For E-Healthcare Security

In recent years, availability and usage of extensive systems for Electronic Healthcare Record (EHR) is increased. In medical centers such hospitals and other laboratories, more health data sets were formed during the treatment process. In order to enhance the standard of the services provided in healthcare, these records where shared and can be used by various users depends on their requirements. As a result, notable issues in the security and privacy where obtained which should be monitored and removed in order to make the use of EHR more effectively. Various researches have been done in the past literature for improving the standards of the security and privacy in E-health systems. In spite of this, it is not completely enhanced. In this paper, a comprehensive analysis is done by selecting the existing approaches and models which were proposed for the security and privacy of the E-healthcare systems. Also, a novel Intelligent-based Access Control Security Model (IBAC) based on multi agents is proposed to maintain and support the security and privacy of E-healthcare systems. This system uses agents in order to maintain security and privacy while accessing the E-health data between the users.

Developing a smart classroom infrastructure to support real-time student collaboration and inquiry: a 4-year design study

K-12 classroom settings are not yet incorporating emerging technologies such as ubiquitous computing, augmented reality, nor even touch surfaces, despite the significant impact that such media have made in many other aspects of our lives. Unfortunately, classroom environments have not generally evolved to support students in the new modes of collaboration, idea sharing, and inquiry that characterize many of our research-based innovations. Responding to this challenge, our research was conducted by a multi-disciplinary design team including educational researchers, a high school physics teacher, and technology designers. We embarked on a series of design-based research projects to investigate a smart classroom infrastructure that scaffolds students and teachers in new forms of collaboration and inquiry, including a substantive role for large projected displays and small touch surfaces, as well as a dependency on students’ physical location within the room. This paper describes our designs, including: (1) the role of large displays for communicating aggregate and ambient information, (2) the role of real-time communication between students, (3) the application of intelligent software agents to enact real-time pedagogical logic, (4) support for learning across contexts, and (5) orchestration of inquiry roles, materials and environments. These designs are particularly relevant for the Learning Sciences community, as they offer insight into how the orchestrated classroom can support new forms of collaborative, cooperative and collective inquiry. One important outcome of this work is a set of design principles for supporting smart classroom research.

Adaptive Tutoring System With Application of Intelligent Agents

In this article, the authors suggest a methodology to adapt learning units to the needs and talents of individual students using an intelligent learning system. Learning personalisation is done based on several factors. Felder and Silverman Learning Styles model is used to create student's profile with conjunction of data mining technologies and previously recorded behaviour of the student. Firstly, the authors perform systematic review of application of intelligent software agents in teaching throughout Clarivate Analytics Web of Science database. Secondly, they present methodologies to personalise learning by means of intelligent technologies. They analyse preferences of students according to Soloman-Felder Learning Styles questionnaire. The resulting model of a student is used in the creation of a personalised learning unit. The model of an adaptive intelligent teaching system based on application of aforementioned technologies is presented in more detail.

Intelektinė daugiaagentė mokymosi sistema, naudojanti edukacinių duomenų tyrybą

In this paper, we present a methodology for personalizing learning in accordance with the needs of individual students by using an intelligent, multi-agent learning system and data mining. Learning personalization is implemented on the basis of several methods. The Felder and Silverman Learning Styles model is used to create student profiles, and the probabilistic suitability indexes are identified to interlink learning components (i.e., learning objects, learning activities and learning environments) with the learning styles of individual students. Other technologies, which were proposed for creating the learning system, are ontologies, recommender system, intelligent software agents and educational data mining/learning analytics. Personalized learning units are referred to here as learning units composed of the learning components that have the highest probabilistic suitability indexes for particular students. In the paper, first, a systematic review on the application of intelligent software agents in learning is performed using the Clarivate Analytics Web of Science database. Second, we present the methods for personalizing the intelligent technologies of learning application, which are used to create optimized learning units for individual students. The developed student profiles and personalized learning units are further corrected by applying the methods and tools of data mining. The model of an intelligent, multi-agent learning system, based on the application of the aforementioned technologies, is presented in more detail. The principal success factors of the proposed methodology are the pedagogically sound vocabularies of learning components, an expert evaluation of the learning components in terms of their suitability for particular students as well as the application of ontologies, recommender systems, intelligent software agents and data mining.

Study of application of intelligent agents in e-learning systems

In this paper, the advantages of using intelligent agents were investigated in order to facilitate and customize suitable electronic learning resources and reinforce collaboration in e-learning environment. Using intelligent agent, learning is personalized based on person’s prior knowledge. E-learning agents monitor electronic learning environment and improve learning and collaboration which is based on learners’ prior knowledge, social features and learning styles. E-learning agents should easily admit of exploration of new learning objects, allowing learners to customize materials presented so that learning and collaboration results can improve in an e-learning environment; it is a learning agent that should offer tangible benefits to organization if operated in online learning or learning environments.

Application of Intelligent Agents in Wireless Prepaid Energy Meter

Prepaid meter (PM) is getting very popular especially in developing countries. There are many advantages to use prepaid meter as opposed to postpaid meter both to the utility provider and to the consumer. Brunei has adopted PM but it is not intelligent and not wireless enabled. Reading meters and topping up balance are still done manually. Utility provider does not have information on the usage statistics and has only limited functionalities in the grid control. So accordingly an intelligent agent based wireless prepaid energy meter been developed using JADE-LEAP Agent development kit allowing agent from utility provider to query wireless energy meter for energy values for every household. These statistics can be used for statistical computation of the power consumed and for policy and future planning. Agent from consumers’ mobile devices can query the energy meter to study the power consumed and for topping up the balance. When the meter reaches the threshold, agent at energy meter would also send messages to alert consumers for topping up through mobile handset and failing to do so will lead to power being cut automatically

Application of intelligent agents in health-care: review

The successful use of intelligent agents in healthcare has attracted researchers to apply this emerging software engineering paradigm in more advanced and complex applications. Main success factor is the natural mapping of real world medical problems into cyber world. Multi-agent architecture can easily model the heterogeneous, distributed and autonomous health care systems. The multi agent systems have been applied from single healthcare activity like knowledge based medical system to complex, multi-component based systems like complete healthcare unit. The use of multi agent systems in health care domain has also opened the ways to find out new applications like personalized and socialized health care systems. This versatile use of multi agent systems has also posed new problems for researchers like; security, communication, and different social issues. This work reviews recent years' research and applications of multi agent systems in healthcare published in different research journals, international conferences, and implemented practically. We reviewed five subdomains and three systems in each subdomain. A set of common parameters of these systems has been extracted and compared to analyze systems' merits and deficiencies. Based on our analysis, we have provided recommendations for multi agent systems applied in healthcare domain. Future research directions for interested researchers and practitioners are also discussed. As our own future research work, we intend to study healthcare and multi agent systems in e-commerce.

Applications of Intelligent Agents in Health Sector-A Review

Health sector is a growing field and health conscience has been a major concern for everyone. Particularly in the health care sector, Information and communication Technology, enabled devices like Smart phones, Tablet PC, Sensors, RFID etc are predominantly used for ease of access and use towards decision processing. So looking into expectations of making devices smarter and intelligent enough for health care application, there has been a growing interest in the use of Software agents in health care application. This Survey paper predominantly concentrates on showing the usage and application of intelligent agent technology in health care sector pertaining to hospital search & appointment, patient health monitoring and mobile health record, with a thorough literature review and appropriate screenshots necessary.

Semantics and Agents Oriented Web Personalization

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.

The Application of Intelligent Agent in Network Platform for Undergraduate's Innovation and Entrepreneurship Education

A new undergraduate's innovation and entrepreneurship education network platform system is designed by using the technology of intelligent Agent. This paper first discusses the necessity, the development system concept and basic principle of intelligent Agent technology, then analyzes the system function and system structure design, finally introduces the design of Agent system.

Applications of Intelligent Agents in Mobile Commerce

Mobile phone usage and its adoption have been growing at exponential rates. It is this exponential growth rate that has led many to predict Mobile Commerce (M-Commerce) as the next major evolution of Electronic Commerce (E-Commerce). While M-Commerce comes rich with unique features, it is currently lacking in usage when compared to traditional e-commerce. There are many challenges that must be addressed in this respect. These challenges are mostly inherent in the mobile devices, communication network, legal and regulatory infrastructure. The use of agents in e-commerce has long been explored in the context, resulting in a number of agent based e-commerce systems. It is not surprising then to note that many researchers believe that the problems that the M-Commerce now faces can be addressed well using agent technology. While there is an abundance of information on the use of agent based systems in other areas, there has been no great surge yet in the use of agent based systems in real world M-Commerce applications. We believe that this slow adoption of this agent technology is due to a lack of standards. There has been a quite an amount of research work carried out in the use of software intelligent agents in the M-Commerce applications like Shopping, Hotel, and Airline industries. These are outlined in the paper with appropriate screenshots and descriptions.

A fault tolerant single-chip intelligent agent with feature extraction capability

Autonomy and adaptability are key features of intelligent agents. Many applications of intelligent agents, such as the control of ambient intelligence environments and autonomous intelligent robotic systems, require the processing of information coming in from many available sensors to produce adequate output responses in changing scenarios. Autonomy, in these cases, applies not only to the ability of the agent to produce correct outputs without human guidance, but also to its ubiquity and/or portability, low-power consumption and integrability. In this sense, an embedded electronic system implementation paradigm can be applied to the design of autonomous intelligent agents in order to satisfy the above mentioned characteristics. However, processing complex computational intelligence algorithms with tight delay constraints in resource-constrained and low power embedded systems is a challenging engineering problem. In this paper a single-chip intelligent agent based on a computationally efficient neuro-fuzzy information processing core is described. The system has been endowed with an information preprocessing module based on Principal Component Analysis (PCA) that permits a substantial reduction of the input space dimensionality with little loss of modeling capability. Moreover, the PCA module has been tested as a means to achieve deep adaptability in changing environment dynamics and to endow the agent with fault tolerance in the presence of sensor failures. For data driven trials and research, a data set obtained from an experimental intelligent inhabited environment has been used as a benchmark system.

B2C E-Commerce Fact-Based Negotiation Using Big Data Analytics and Agent-Based Technologies

The focus of this study is application of intelligent agent in negotiation between buyer and seller in B2C Commerce using big data analytics. The developed model is used to conduct negotiations on behalf of prospective buyers and sellers using analytics to improve negotiations to meet the practical requirements. The objective of this study is to explore the opportunities of using big data and business analytics for negotiation, where big data analytics can be used to create new opportunities for bidding. Using big data analytics sellers may learn to predict the buyers’ negotiation strategy and therefore adopt optimal tactics to pursue results that are to their best interests. An experimental design is used to collect intelligent data that can be used in conducting the negotiation process. Such approach will improve quality of negotiation decisions for both parties.

An Agent-Based Framework for Supply Chain Cooperation

The importance of cooperation in the supply chain has led scholars to suggest diverse approaches for problems in the collaboration process. Cooperation refers to the integration of different parts of an organization or different organizations in supply chain to accomplish a collective set of tasks and to achieve mutual benefits. The use of modern information technology (IT) decision support systems is fast becoming an indispensable tool for designing and managing complex supply chain systems today. This study describes a model of intelligent framework for cooperation in the supply chain environment. The aim of the paper is to demonstrate that agent technology can represent the supply chains by (a) reviewing intelligent agent applications for supply chain and (b) illustrating how a multi-agent system can provides a solution for supply chain cooperation. We review and synthesis existing applications in comparison to traditional and Internet-based technologies and critically evaluate agent technology applicability for supply chain management. This paper thus provides an intelligent framework for extended enterprise cooperation (i-SEEC) by adopting the techniques of the Semantic Web service and Multi-agents system. The proposed system can integrate different information technologies to make its behavior more intelligent and to catch more useful information from supply chain actors.

Accounting information systems: An intelligent agents approach

The purpose of this paper is to present new approaches in the development of accounting information systems to enable better data management and information creation. The objective is achieved by applying an object-oriented modeling with the use of intelligent agents, according to the needs of users of accounting information. In development of this work, it was observed that a structure based on objects and using intelligent agents enables the development of reports for different users, with gains in the quality of information developed. The major limitation of this work is that it was done on a theoretical basis; however, the practical aspect is yet to be carried out due to the extent of its development. The great advantage of working is to use an object-oriented modeling with simultaneous application of intelligent agents, who carry on the development and analysis of accounting. Thus, the accounting information system is able to meet fully the qualities needed to users, without loss of comprehensibility, relevance, reliability and comparability, even with changes in business model or in accounting standards used. Furthermore, the development of new intelligent agents enables a retrospect on previous year's analysis. Key words: Accounting information systems, DCA (debit-credit accounting) model, resource, events and agents (REA) model; intelligent agents, object-oriented.

A fuzzy goal programming for optimizing service industry market using virtual intelligent agent

The application of intelligent agents in decision-making has gained extensive interest. Intelligent agents function as decision aids to automate variety of tasks and facilitate decision-making. Service industry market analysis was carried out investigating the included components. Here, we consider a market in which customer and vendor are the two components. To conceptualize the interaction between customer and vendor, a virtual intelligent agent is proposed to perform optimization decisions namely, minimizing the total delivery cost, minimizing the total delivery time, and maximizing the total profit. The optimization is fulfilled with respect to several attributes related to the customer and vendor intelligent agents. The multi-objective model is optimized using fuzzy goal programming. The validity and applicability of the proposed mechanism is illustrated in a numerical example.

Are intelligent agents the key to optimizing building HVAC system performance?

This article describes the development and implementation of a simulation testbed used to study the concept of employing intelligent agents to optimize the performance of building HVAC systems. One-day simulated cost savings results are presented for intelligent agents employing both a simple optimization method and an advanced optimization method. The potential benefits and problems associated with each method are discussed, and recommendations are made for future research efforts leading to the application of intelligent agents in real building.

Application of Intelligent Agents in Hospital Appointment Scheduling System

Application of Intelligent Agents in Hospital Appointment Scheduling System