Knowledge Management Agent Research Articles

PACA-ITS: A Multi-Agent System for Intelligent Virtual Laboratory Courses

This paper describes an intensive design leading to the implementation of an intelligent lab companion (ILC) agent for an intelligent virtual laboratory (IVL) platform. An IVL enables virtual labs (VL) to be used as online research laboratories, thereby facilitating and improving the analytical skills of students using agent technology. A multi-agent system enhances the capability of the learning system and solves students’ problems automatically. To ensure an exhaustive Agent Unified Modeling Language (AUML) design, identification of the agents’ types and responsibilities on well-organized AUML strategies is carried out. This work also traces the design challenge of IVL modeling and the ILC agent functionality of six basic agents: the practical coaching agent (PCA), practical dispatcher agent (PDA), practical interaction and coordination agent (PICA), practical expert agent (PEA), practical knowledge management agent (PKMA), and practical inspection agent (PIA). Furthermore, this modeling technique is compatible with ontology mapping based on an enabling technology using the Java Agent Development Framework (JADE), Cognitive Tutor Authoring Tools (CTAT), and Protégé platform integration. The potential Java Expert System Shell (Jess) programming implements the cognitive model algorithm criteria that are applied to measure progress through the CTAT for C++ programming concept task on IVL and successfully deployed on the TutorShop web server for evaluation. The results are estimated through the learning curve to assess the preceding knowledge, error rate, and performance profiler to engage cognitive Jess agent efficiency as well as practicable and active decisions to improve student learning.

Agent-based knowledge management system with APQP: implementation of semiconductor manufacturing services industry

Future challenges posed to semiconductor manufacturing services firms demands a system framework which could not only introduce, development, and design new products into mass production with customer-acceptable quality level and profitable approaches, but also re-use best practice in the shop floor to continuously optimise the existing order fulfilment process with effectiveness and efficiency. Advanced product quality planning (APQP) tool integrated with agent-based knowledge management (KM) intelligence develops a systematic framework that responds to such challenges. We propose an APQP tool working with an agent-based knowledge management system (ABKMS) which builds on organisational knowledge resources and works with the APQP concept as well as KM agents. The proposed framework reflects how an APQP tool with KM agents seeks significant inroads into process knowledge repository to recommend a solution for decision making in delivering semiconductor manufacturing services in customer selection, parts and material selection, bill of material, equipments, and tools selection, with a modified APQP concept to work out the approach to be used to develop the streamlined and common process.

Distributed multi-agent system approach for sheet metal forming

In this study, a distributed multi-agent system (DMAS) for sheet metal forming is proposed. The system consists of functional agents such as die design agent, knowledge management agent, validation and verification agent, product description agent, operation planning agent, calculating and dimensioning agent, artificial intelligence agent, assembly and disassembly agent. Also there is a design mediator. Each of the functional agents is enhanced software and can be considered as an expert of the classical die design. This paper provides the theoretical framework for future research. This enhanced system has been implemented on a simple sheet metal part. So, it can be seen that die design of sheet metal parts can successfully be realized using a multi-agent system.

Intelligent alarms integrated in a multi-agent architecture for diabetes management

This paper describes the development of an intelligent agent that interprets blood glucose monitoring data received by a telemedicine-based diabetes management service. The agent generates automatic alarms when some deviations in the patient status are detected. The agent combines different methods to produce data summaries and automatic alarms based on statistics, rule-based techniques and model-based techniques. The rule-based analysis allows the detection of severe abnormalities using different time scales depending on the quality of the received information. The model-based analysis uses a physiological qualitative model implemented with a causal probabilistic network that detects deviations in the ‘insulin effectiveness’ along days. The KM (Knowledge Management) agent was tested with data from 11 patients with diabetes that used a telemedicine service during 1 year. The KM agent detected anomalous situations in the 100% of the cases where a therapy modification was decided by the healthcare professional; the agent detected abnormal data in 37% of transmissions, being able to decrease professionals’ workload due to telemedicine. The advantages of an automatic response integrated in a telemedicine service are that it focuses doctors’ and patients’ attention on abnormal data and gives instantaneous feedback to patients reinforcing the education and the motivation aspects of the therapy.

Software agents for knowledge management: coordination in multi-agent supply chains and auctions

A fundamental question that must be addressed in software agents for knowledge management is coordination in multi-agent systems. The coordination problem is ubiquitous in knowledge management, such as in manufacturing, supply chains, negotiation, and agent-mediated auctions. This paper summarizes several multi-agent systems for knowledge management that have been developed recently by the author and his collaborators to highlight new research directions for multi-agent knowledge management systems. In particular, the paper focuses on three areas of research: • Coordination mechanisms in agent-based supply chains. How do we design mechanisms for coordination, information and knowledge sharing in supply chains with self-interested agents? What would be a good coordination mechanism when we have a non-linear structure of the supply chain, such as a pyramid structure? What are the desirable properties for the optimal structure of efficient supply chains in terms of information and knowledge sharing? Will DNA computing be a viable tool for the analysis of agent-based supply chains? • Coordination mechanisms in agent-mediated auctions. How do we induce cooperation and coordination among various self-interested agents in agent-mediated auctions? What are the fundamental principles to promote agent cooperation behavior? How do we train agents to learn to cooperate rather than program agents to cooperate? What are the principles of trust building in agent systems? • Multi-agent enterprise knowledge management, performance impact and human aspects. Will people use agent-based systems? If so, how do we coordinate agent-based systems with human beings? What would be the impact of agent systems in knowledge management in an information economy?

EMB3/389: Information Systems for Evidence-based Healthcare: status, issues and perspectives

IntroductionIn the United Kingdom, the National Health Service (NHS) has embarked on the formation of health action zones for the delivery of good quality community-centric healthcare. It is recognised that the evidence-based healthcare practice is critical in this venture, and the optimistic projection is that community-centric healthcare encompassing medical, dental, nursing, health visiting, optical and pharmaceutical services will be brought under the evidence-based healthcare practice framework. The evidence-based medicine and its practice in its 'first wave' with its six steps provided a paradigm shift in the clinical practice by integrating experiential and external evidence with clinical practice to arrive at clinical decisions and establish disease management framework. The internet was rightly considered as the key player in the evidence-based healthcare practice. The shortcomings of this global system has constrained the wide-spread application of the evidence-based practice.MethodsWe will first take an in-depth look at the relevance, quality and accessibility issues, by presenting examples from respiratory and metabolic disease domains, particularly from the classes of paediatric metabolic disorders. While analysing the information presented, we will also assess to what degree the information needs of clinicians as well as patient/home-carers are met. We will examine what is required in terms of structure, protocols, information storage and access to meet the two often disparate needs.ResultsWe will argue that the information should be in a form that enables their effective assimilation thereby enhancing the usage of the evidence-based practice. Concepts of componentware, model-based information- bayesian causal graphs will presented with examples. Examples of emerging database implementations will be referred to in these examples. Our on-going research work on MEDINFONET, and models of domain-specific software agents for knowledge management will be presented.DiscussionThe service-centric model of the next generation internet presents a bright perspective. From the evidence-based healthcare practice point-of-view, its differential service (diff-serv) facility with emphasis on classes of services will largely meet the speed of access requirement. The 'object web' with data integration facility, digital libraries, domain-specific search agents etc.. will provide a better information quality. We argue that models and metrics for information systems and its environment are needed, and in this connection present a five-layer maturity model for evidence-based healthcare practice.