Hybrid Multi-Agents and Case Based Reasoning for Aiding Green Practice in Institutions of Higher Learning

Sustainability is a concern that has been raised in many domains especially in institutions of higher learning such as universities. Hence, universities are implementing Green practices to promote sustainability. Similarly Green practice implementation in universities for attaining sustainability has been the priority for most universities across the world, mainly in ensuring the effectiveness and efficiency of Information Technology (IT) related service. Over the years, a few approaches have been developed to facilitate Green practice in institutions of higher learning, however these approaches are not autonomous and do not provide adequate information on Green implementation initiatives. Moreover, institutions of higher learning utilize manual checklist assessment questionnaire to evaluate their current Green practice. Therefore, this study proposes a system model that integrates hybrid multi-agent and Case Based Reasoning (CBR). The CBR technique facilitates Green implementation by providing information on how institution of higher learning can adopt Green practices initiative, whereas software agents autonomously assess the current Green practice initiative implemented in institutions of higher learning. Findings from this paper show how the hybrid multi-agent and CBR aid universities implement Green practice for sustainability attainment in institutions of higher learning

Applying hybrid case-based reasoning in agent-based negotiations for supply chain management

In recent years, enormous research effort has been spent on the development of multi-agent systems to automate buyer-seller negotiations in supply chain management (SCM) applications. In many of these agent-based negotiation systems, the negotiation process is restricted to the stage when agents interact to exchange bargaining offers; activities in the pre-bargaining and post-bargaining stages are ignored. With a more comprehensive perspective, the negotiation lifecycle comprises a number of phases including the pre- and post-bargaining phases, in addition to the phase when participants interact to bargain. In this paper, a hybrid case-based reasoning approach is applied in the pre- and post-negotiation phases to support adaptive negotiation strategy for buyer-seller negotiations in SCM applications. When a new negotiation problem arrives, a similar previous negotiation case is retrieved from the case database and its solutions are recommended for inferring the negotiation parameters. The recommended parameters have to be adjusted to suit the new negotiation problem. Subsequent to negotiation completion, negotiation parameters and the negotiation outcome are analyzed and evaluated. After the evaluation, the new negotiation case, including the problem descriptions and solutions, is retained in the case database for future applications. © 2010 Elsevier Ltd. All rights reserved.link_to_subscribed_fulltex