Towards the development of agent-based organizations through MDD

Electronic version of an article published as International Journal on Artificial Intelligence Tools, 22, 2, 2013, DOI 10.1142/S0218213013500024 © World Scientific Publishing Company http://www.worldscientific.com/worldscinet/ijaitVirtual Organizations are a mechanism where agents can demonstrate their social skills since they can work in a cooperative and collaborative way. Nonetheless, the development of organizations using Multi-Agent Systems (MAS) requires extensive experience in different methodologies and platforms. Model-Driven Development (MDD) is a technique for generating application code that is developed from basic models and meta-models using a variety of automatic transformations. This paper presents an approach to develop and deploy organization-oriented Multi-Agent Systems using a model-driven approach. Based on this idea, we introduce a relatively generic agent-based meta-model for a Virtual Organization, which was created by a comprehensive analysis of the organization-oriented methodologies used in MAS. Following the MDD approach, the concepts and relationships obtained were mapped into two different platforms available for MAS development, allowing the validation of our proposal. In this way, the resultant approach can generate Virtual Organization deployments from unified meta-models, facilitating the development process of agent-based software from the user point of view.This work was partially supported by TIN2009-13839-C03-01 and PROMETEO/2008/051 projects of the Spanish government and CONSOLIDER-INGENIO 2010 under grant CSD2007-00022.Agüero, J.; Carrascosa Casamayor, C.; Rebollo Pedruelo, M.; Julian Inglada, VJ. (2013). Towards the development of agent-based organizations through MDD. International Journal on Artificial Intelligence Tools. 22(2):1-34. https://doi.org/10.1142/S0218213013500024S134222Argente, E., Julian, V., & Botti, V. (2006). Multi-Agent System Development Based on Organizations. Electronic Notes in Theoretical Computer Science, 150(3), 55-71. doi:10.1016/j.entcs.2006.03.005Bézivin, J. (2005). On the unification power of models. Software & Systems Modeling, 4(2), 171-188. doi:10.1007/s10270-005-0079-0Bresciani, P., Perini, A., Giorgini, P., Giunchiglia, F., & Mylopoulos, J. (2004). Tropos: An Agent-Oriented Software Development Methodology. Autonomous Agents and Multi-Agent Systems, 8(3), 203-236. doi:10.1023/b:agnt.0000018806.20944.efFoster, I., Kesselman, C., & Tuecke, S. (2001). The Anatomy of the Grid: Enabling Scalable Virtual Organizations. The International Journal of High Performance Computing Applications, 15(3), 200-222. doi:10.1177/109434200101500302Hahn, C., Madrigal-Mora, C., & Fischer, K. (2008). A platform-independent metamodel for multiagent systems. Autonomous Agents and Multi-Agent Systems, 18(2), 239-266. doi:10.1007/s10458-008-9042-0HORLING, B., & LESSER, V. (2004). A survey of multi-agent organizational paradigms. The Knowledge Engineering Review, 19(4), 281-316. doi:10.1017/s0269888905000317Huhns, M. N., & Singh, M. P. (2005). Service-oriented computing: key concepts and principles. IEEE Internet Computing, 9(1), 75-81. doi:10.1109/mic.2005.21Huhns, M. N., Singh, M. P., Burstein, M., Decker, K., Durfee, E., Finin, T., … Zavala, L. (2005). Research Directions for Service-Oriented Multiagent Systems. IEEE Internet Computing, 9(6), 65-70. doi:10.1109/mic.2005.132Kolp, M., Giorgini, P., & Mylopoulos, J. (2006). Multi-Agent Architectures as Organizational Structures. Autonomous Agents and Multi-Agent Systems, 13(1), 3-25. doi:10.1007/s10458-006-5717-6OHTANI, T., CASE, S., AZARMI, N., & THINT, M. (2002). AN INTELLIGENT SYSTEM FOR MANAGING AND UTILIZING INFORMATION RESOURCES OVER THE INTERNET. International Journal on Artificial Intelligence Tools, 11(01), 117-138. doi:10.1142/s0218213002000800Omicini, A., Ricci, A., & Viroli, M. (2005). RBAC for Organisation and Security in an Agent Coordination Infrastructure. Electronic Notes in Theoretical Computer Science, 128(5), 65-85. doi:10.1016/j.entcs.2004.11.045Papazoglou, M. P., & Georgakopoulos, D. (2003). Introduction. Communications of the ACM, 46(10), 24. doi:10.1145/944217.944233Papazoglou, M. P., Traverso, P., Dustdar, S., & Leymann, F. (2007). Service-Oriented Computing: State of the Art and Research Challenges. Computer, 40(11), 38-45. doi:10.1109/mc.2007.400Selic, B. (2003). The pragmatics of model-driven development. IEEE Software, 20(5), 19-25. doi:10.1109/ms.2003.1231146SKARMEAS, N. P., & CLARK, K. L. (2002). COMPONENT BASED AGENT CONSTRUCTION. International Journal on Artificial Intelligence Tools, 11(01), 139-163. doi:10.1142/s0218213002000812Zambonelli, F., Jennings, N. R., & Wooldridge, M. (2003). Developing multiagent systems. ACM Transactions on Software Engineering and Methodology, 12(3), 317-370. doi:10.1145/958961.95896

Updates on naringinase : structural and biotechnological aspects

Naringinases has attracted a great deal of attention in recent years due to its hydrolytic activities which include the production of rhamnose, and prunin and debittering of citrus fruit juices. While this enzyme is widely distributed in fungi, its production from bacterial sources is less commonly known. Fungal naringinase are very important as they are used industrially in large amounts and have been extensively studied during the past decade. In this article, production of bacterial naringinase and potential biotechnological applications are discussed. Bacterial rhamnosidases are exotype enzymes that hydrolyse terminal non-reducing &Icirc;&plusmn;-l-rhamnosyl groups from &Icirc;&plusmn;-l-rhamnose containing polysaccharides and glycosides. Structurally, they are classified into family 78 of glycoside hydrolases and characterized by the presence of Asp567 and Glu841 in their active site. Optimization of fermentation conditions and enzyme engineering will allow the development of improved rhamnosidases for advancing suggested industrial applications.<br /