Design of a multi-agent system using the "MaSE" method for learners' metacognitive help

This article addresses a multi-agent approach to solving the problem of integrating metacognitive incentives into Learning Management System. The behavior of the teacher in a classroom-teaching situation, where teacher adopting the competency-based approach, is characterized by a set of didactic interventions dynamically adaptable according to the actions-reactions of the learners. These interventions are continually subjected to perfection by experience. In this article, we are interested in modeling the multi-agent system in order to help the learners develop their metacognitive skills in a continuous way. The purpose of this system is to supervise the activities and statements of the learner and communicate them to the metacognitive agent. The latter focuses on the assessment of the learner's metacognitive skills in order to trigger, automatically, metacognitive incentives to provide help messages. Integrating the agent for metacognitive control and assistance, allows learners to maintain motivation and confidence, and elicit their attention to the importance of metacognitive skills during learning activity. The "MaSE" methodology and the "agentTool" are used to model the multi-agent system

Talking about the likelihood of risks:an agent-based simulation of discussion processes in risk workshops

Purpose This paper aims to explore drivers of the effectiveness of risk assessments in risk workshops. Design/methodology/approach This study uses an agent-based model to simulate risk assessments in risk workshops. Combining the notions of transactive memory and the ideal speech situation, this study establishes a risk assessment benchmark and then investigates real-world deviations from this benchmark. Specifically, this study models limits to information transfer, incomplete discussions and potentially detrimental group characteristics, as well as interaction patterns. Findings First, limits to information transfer among workshop participants can prevent a correct consensus. Second, increasing the required number of stable discussion rounds before an assessment improves the correct assessment of high but not low likelihood risks. Third, while theoretically advantageous group characteristics are associated with the highest assessment correctness for all risks, theoretically detrimental group characteristics are associated with the highest assessment correctness for high likelihood risks. Fourth, prioritizing participants who are particularly concerned about the risk leads to the highest level of correctness. Originality/value This study shows that by increasing the duration of simulated risk workshops, the assessments change – as a rule – from underestimating to overestimating risks, unraveling a trade-off for risk workshop facilitators. Methodologically, this approach overcomes limitations of prior research, specifically the lack of an assessment and process benchmark, the inability to disentangle multiple effects and the difficulty of capturing individual cognitive processes

Development of Autonomous Multi Agent System for Multi-Hazard Risk Assessment

Developing autonomous multi agent systems are to be considered anadvancement of multi agent systems can be applied in both the physical and the logicalworld. Constructions of multi hazard risk assessment using spatial data for disastermanagement have a problem of effective communication because of implicitknowledge. Risk assessment is the determination of quantitative or qualitative value ofrisk related to a concrete situation and a recognized hazard. Multi hazard riskassessment requires commonsense knowledge related with the hazard. This complicatesthe effective communication of data to the user in real-time machine processing insupport of disaster management. The aim of the approach is to identify the influences ofdeveloping autonomous multi agent systems for risk assesmnet in disaster management.The objectives should a) contribute to a better understanding of the transformationprocesses in commonsense knowledge related with a hazard and b) provide effectivecommunication of data to the user in real-time machine processing in support of disastermanagement.In this paper we present a metodology to modeling commonsenseknowledge in Multi hazard risk assessment using Autonomous multi agent system. Thisgives three-phase knowledge modeling approach for modeling commonsenseknowledge in, which enables holistic approach for disaster management. At the initialstage autonomous agents are initialized to convert commonsense knowledge based onmulti hazards into a questionnaire. Removing dependencies among the questions aremodeled using principal component analysis. Classification of the knowledge isprocessed through fuzzy logic agent, which is constructed on the basis of principalcomponents. Further explanations for classified knowledge are derived by agent basedon expert system technology. We have implemented the system using FLEX expertsystem shell, SPSS, XML and VB. This paper describes one such approach usingclassification of human constituents in Ayurvedic medicine. Evaluation of the systemhas shown 77% accuracy.Key words: Autonomous multi agent systems, Multi hazards, risk assessment,commonsense knowledge, Fuzzy logi

Facilitating mas complete life cycle through the protégé-prometheus approach

The approach of this paper aims to support the complete multi-agent systems life cycle, integrated by two existing and widely accepted tools, Protégé Ontology Editor and Knowledge-Base Framework, and Prometheus Development Kit. A general sequence of steps facilitating application creation is proposed in this paper. We propose that it seems reasonable to integrate all traditional software development stages into one single methodology. This view provides a general approach for MAS creation, starting with problem definition and resulting in program coding, deployment and maintenance. The proposal is successfully being applied to situation assessment issues, which has concluded in an agent-based decision-support system for environmental impact evaluation

Vive la Différence? Structural Diversity as a Challenge for Metanormative Theories

Decision-making under normative uncertainty requires an agent to aggregate the assessments of options given by rival normative theories into a single assessment that tells her what to do in light of her uncertainty. But what if the assessments of rival theories differ not just in their content but in their structure -- e.g., some are merely ordinal while others are cardinal? This paper describes and evaluates three general approaches to this "problem of structural diversity": structural enrichment, structural depletion, and multi-stage aggregation. All three approaches have notable drawbacks, but I tentatively defend multi-stage aggregation as least bad of the three

Risk assessment and relationship management: practical approach to supply chain risk management

The literature suggests the need for incorporating the risk construct into the measurement of organisational performance, although few examples are available as to how this might be undertaken in relation to supply chains. A conceptual framework for the development of performance and risk management within the supply chain is evolved from the literature and empirical evidence. The twin levels of dyadic performance/risk management and the management of a portfolio of performance/risks is addressed, employing Agency Theory to guide the analysis. The empirical evidence relates to the downstream management of dealerships by a large multinational organisation. Propositions are derived from the analysis relating to the issues and mechanisms that may be employed to effectively manage a portfolio of supply chain performance and risks