Coalition Formation for Cooperative Information Agent-Based Systems

The communication technology evolution led to an increase of the carried out services’ and tasks’ number. The aim of actual research in the cooperation and particularly the negotiation between agents is to reach a coherent global state of the multiagent system by favoring agents’ synergy. In this paper, we propose a coalition formation-based negotiation model for the task allocation in the cooperative information agent-based systems. In this model, the agent that activates a negotiation seeks partners for achieving a complex task. The way that the partners take part in a coalition is done one by one according to the choice of all the coalition members. This choice is based on a multicriterion analysis. Some obtained experimental results show the suggested model performances

Formal verification of the extension of iStar to support Big data projects

Identifying all the right requirements is indispensable for the success of anysystem. These requirements need to be engineered with precision in the earlyphases. Principally, late corrections costs are estimated to be more than 200times as much as corrections during requirements engineering (RE). EspeciallyBig data area, it becomes more and more crucial due to its importance andcharacteristics. In fact, and after literature analyzing, we note that currentsRE methods do not support the elicitation of Big data projects requirements. Inthis study, we propose the BiStar novel method as extension of iStar to under-take some Big data characteristics such as (volume, variety ...etc). As a firststep, we identify some missing concepts that currents requirements engineeringmethods do not support. Next, BiStar, an extension of iStar is developed totake into account Big data specifics characteristics while dealing with require-ments. In order to ensure the integrity property of BiStar, formal proofs weremade, we perform a bigraph based description on iStar and BiStar. Finally, anapplication is conducted on iStar and BiStar for the same illustrative scenario.The BiStar shows important results to be more suitable for eliciting Big dataprojects requirements

Approaches through which anticipation informs climate governance in South Asia

This report presents the RE-IMAGINE research in one of its four regions: South Asia. RE-IMAGINE builds on climate foresight expertise of the Climate Change, Agriculture and Food Security (CCAFS) Program and analyses the role of foresight in climate governance across the globe. Scenarios and many other methods and tools are used today to imagine climate futures and develop strategies for realizing new futures while governing climate change. With the proliferation of these processes in sustainability-related research and planning contexts, scrutiny of their role in steering climate actions in the present becomes increasingly important. How can the benefits and challenges of these processes of anticipation be better understood as governance interventions? At the same time, research into anticipatory climate governance processes in the Global South has remained very limited, while these regions are most vulnerable to climate change. The RE-IMAGINE report therefore examines processes of anticipation in four regions of the Global South. The research question we answer in this report is: ‘through what approaches are diverse processes of anticipation used to govern climate change in diverse South Asian contexts?’. In order to answer this question, we first examine what methods and tools are used to anticipate climate futures and their role in climate policy and decision-making. We then closely examine three case studies to understand their approaches to anticipatory governance. Additionally, we present the results of two regional meetings with stakeholders where we discussed the challenges that exist in each country to practice anticipatory climate governance and the opportunities to strengthen capacities in this field. Finally, we present recommendations for strengthening processes of anticipatory climate governance in the region

Composition of Aspectual Requirements: A Multi-criteria Process for Conflict Resolution.

In Aspect Oriented Software Development, aspects are not only used at the programming level but also tend to arise at the requirements analysis and software architecture design. We previously proposed an approach named AspeCiS (An aspect-oriented Approach to Develop a Cooperative Information System) to develop a Cooperative Information System from existing Information Systems by using their artifacts such as existing requirements and design elements. This approach include an important step in which the aspectual requirements composition problem is considered to be one of the remaining challenges. So, when multiple aspectual requirements share the same join point, undesired behavior may emerge and a conflict resolution process must be triggered. This study presents a conflict resolution process among aspects during the requirements engineering level: A priority value is computed for each aspect and it allows identifying a dominant aspectual requirement on the basis of stakeholder priority. This process is more formal than those currently proposed, which requires a trade-off negotiation to resolve conflicts

Coalition Formation for Cooperative Information Agent-Based Systems

Abstract: The communication technology evolution led to an increase of the carried out services ’ and tasks ’ number. The aim of actual research in the cooperation and particularly the negotiation between agents is to reach a coherent global state of the multiagent system by favoring agents ’ synergy. In this paper, we propose a coalition formation-based negotiation model for the task allocation in the cooperative information agent-based systems. In this model, the agent that activates a negotiation seeks partners for achieving a complex task. The way that the partners take part in a coalition is done one by one according to the choice of all the coalition members. This choice is based on a multicriterion analysis. Some obtained experimental results show the suggested model performances

An agent-based approach for personalised and adaptive learning

International audienceMost of learning systems deliver the same learning materials when targeting the same learning unit. It turned out that the learning process could significantly be improved if learning content could be specifically personalised and adapted to individual learners' domain knowledge and capabilities. Few learning systems introduce teaching strategies to satisfy individual learners' requirements. In an attempt to overcome these limitations, we propose a multi-agent system, which is based on learning styles for its adaptability and on domain knowledge for its personalisation. In this paper, we describe the design and implementation of this multi-agent based learning system. In particular we discuss the learning resources collecting process, the personalised process and the adaptive process. The system has been tested through several functional experiments, and the analysis of the simulation study indicates that the approach is able to handle personalised and adaptive learning

Resource management policies to increase provider’s gain in a Cloud Coalition

International audienc

An agent-based architecture for resource allocation in Cloud Computing

International audienceAn agent-based architecture for resource allocation in Cloud Computin

Intelligent Mechanism for Cloud Federation and Requirements Changes Management.

International audienc

An agent-based architecture for resource allocation in Cloud Computing

International audienceAn agent-based architecture for resource allocation in Cloud Computin