Complexity and Philosophy

The science of complexity is based on a new way of thinking that stands in sharp contrast to the philosophy underlying Newtonian science, which is based on reductionism, determinism, and objective knowledge. This paper reviews the historical development of this new world view, focusing on its philosophical foundations. Determinism was challenged by quantum mechanics and chaos theory. Systems theory replaced reductionism by a scientifically based holism. Cybernetics and postmodern social science showed that knowledge is intrinsically subjective. These developments are being integrated under the header of “complexity science”. Its central paradigm is the multi-agent system. Agents are intrinsically subjective and uncertain about their environment and future, but out of their local interactions, a global organization emerges. Although different philosophers, and in particular the postmodernists, have voiced similar ideas, the paradigm of complexity still needs to be fully assimilated by philosophy. This will throw a new light on old philosophical issues such as relativism, ethics and the role of the subject

General systems perspective on achieving continuous synergy in a project organisation

Studies of construction labour productivity have revealed that limited predictability and multi-agent social complexity make long-range planning of construction projects extremely inaccurate. Fire-fighting, a cultural feature of construction project management, social and structural diversity of involved permanent organizations, and structural temporality all contribute towards relational failures and frequent changes. The main purpose of this paper is therefore to demonstrate that appropriate construction planning may have a profound synergistic effect on structural integration of a project organization. Using the general systems theory perspective it is further a specific objective to investigate and evaluate organizational effects of changes in planning and potentials for achieving continuous project-organizational synergy. The newly developed methodology recognises that planning should also represent a continuous, improvement-leading driving force throughout a project. The synergistic effect of the process planning membership duality fostered project-wide integration, eliminated internal boundaries, and created a pool of constantly upgrading knowledge. It maintained a creative environment that resulted in a number of process-related improvements from all parts of the organization. As a result labour productivity has seen increases of more than 30%, profits have risen from an average of 12% to more than 18%, and project durations have been reduced by several days

Challenges for adaptation in agent societies

The final publication is available at Springer via http://dx.doi.org/[insert DOIAdaptation in multiagent systems societies provides a paradigm for allowing these societies to change dynamically in order to satisfy the current requirements of the system. This support is especially required for the next generation of systems that focus on open, dynamic, and adaptive applications. In this paper, we analyze the current state of the art regarding approaches that tackle the adaptation issue in these agent societies. We survey the most relevant works up to now in order to highlight the most remarkable features according to what they support and how this support is provided. In order to compare these approaches, we also identify different characteristics of the adaptation process that are grouped in different phases. Finally, we discuss some of the most important considerations about the analyzed approaches, and we provide some interesting guidelines as open issues that should be required in future developments.This work has been partially supported by CONSOLIDER-INGENIO 2010 under grant CSD2007-00022, the European Cooperation in the field of Scientific and Technical Research IC0801 AT, and projects TIN2009-13839-C03-01 and TIN2011-27652-C03-01.Alberola Oltra, JM.; Julian Inglada, VJ.; García-Fornes, A. (2014). Challenges for adaptation in agent societies. Knowledge and Information Systems. 38(1):1-34. https://doi.org/10.1007/s10115-012-0565-yS134381Aamodt A, Plaza E (1994) Case-based reasoning; foundational issues, methodological variations, and system approaches. AI Commun 7(1):39–59Abdallah S, Lesser V (2007) Multiagent reinforcement learning and self-organization in a network of agents. 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Evaluating how agent methodologies support the specification of the normative environment through the development process

[EN] Due to the increase in collaborative work and the decentralization of processes in many domains, there is an expanding demand for large-scale, flexible and adaptive software systems to support the interactions of people and institutions distributed in heterogeneous environments. Commonly, these software applications should follow specific regulations meaning the actors using them are bound by rights, duties and restrictions. Since this normative environment determines the final design of the software system, it should be considered as an important issue during the design of the system. Some agent-oriented software engineering methodologies deal with the development of normative systems (systems that have a normative environment) by integrating the analysis of the normative environment of a system in the development process. This paper analyses to what extent these methodologies support the analysis and formalisation of the normative environment and highlights some open issues of the topic.This work is partially supported by the PROMETEOII/2013/019, TIN2012-36586-C03-01, FP7-29493, TIN2011-27652-C03-00, CSD2007-00022 projects, and the CASES project within the 7th European Community Framework Program under the grant agreement No 294931.Garcia Marques, ME.; Miles, S.; Luck, M.; Giret Boggino, AS. (2014). Evaluating how agent methodologies support the specification of the normative environment through the development process. Autonomous Agents and Multi-Agent Systems. 1-20. https://doi.org/10.1007/s10458-014-9275-zS120Cossentino, M., Hilaire, V., Molesini, A., & Seidita, V. (Eds.). (2014). Handbook on agent-oriented design processes (Vol. VIII, 569 p. 508 illus.). Berlin: Springer.Akbari, O. (2010). A survey of agent-oriented software engineering paradigm: Towards its industrial acceptance. 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Verhagen (Eds.), Normative multi-agent systems, number 09121 in Dagstuhl seminar proceedings.Boella, G., Torre, L., & Verhagen, H. (2006). Introduction to normative multiagent systems. Computational and Mathematical Organization Theory, 12(2–3), 71–79.Bogdanovych, A., Esteva, M., Simoff, S., Sierra, C., & Berger, H. (2008). A methodology for developing multiagent systems as 3d electronic institutions. In M. Luck & L. Padgham (Eds.), Agent-Oriented Software Engineering VIII (Vol. 4951, pp. 103–117). Lecture Notes in Computer Science. Berlin: Springer.Boissier, O., Padget, J., Dignum, V., Lindemann, G., Matson, E., Ossowski, S., Sichman, J., & Vazquez-Salceda, J. (2006). Coordination, organizations, institutions and norms in multi-agent systems. LNCS (LNAI) (Vol. 3913).Bordini, R. H., Fisher, M., Visser, W., & Wooldridge, M. (2006). Verifying multi-agent programs by model checking. In Autonomous agents and multi-agent systems (Vol. 12, pp. 239–256). 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Utility-Based Mechanism for Structural Self-Organization in Service-Oriented MAS

Structural relations established among agents influence the performance of decentralized service discovery process in multiagent systems. Moreover, distributed systems should be able to adapt their structural relations to changes in environmental conditions. In this article, we present a service-oriented multiagent systems, where agents initially self-organize their structural relations based on the similarity of their services. During the service discovery process, agents integrate a mechanism that facilitates the self-organization of their structural relations to adapt the structure of the system to the service demand. This mechanism facilitates the task of decentralized service discovery and improves its performance. Each agent has local knowledge about its direct neighbors and the queries received during discovery processes. With this information, an agent is able to analyze its structural relations and decide when it is more appropriate to modify its direct neighbors and select the most suitable acquaintances to replace them. The experimental evaluation shows how this self-organization mechanism improves the overall performance of the service discovery process in the system when the service demand changesThis work is partially supported by the Spanish Ministry of Science and Innovation through grants CSD2007-0022 (CONSOLIDER-INGENIO 2010), TIN2012-36586-C03-01, TIN2012-36586-C03-01, TIN2012-36586-C03-02, PROMETEOII/2013/019, and FPU grant AP-2008-00601 awarded to E. Del Val.Del Val Noguera, E.; Rebollo Pedruelo, M.; Vasirani, M.; Fernández, A. (2014). Utility-Based Mechanism for Structural Self-Organization in Service-Oriented MAS. ACM Transactions on Autonomous and Adaptive Systems. 9(3):1-24. https://doi.org/10.1145/2651423S12493Sherief Abdallah and Victor Lesser. 2007. 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The key roles of economic and social organization, producer and consumer behaviour towards a Health-Agriculture-Food-Environment Nexus: recent advances and future prospects

We discuss in this paper the role of the economic and social organization in agriculture and the food industry, in relation with the Health-Agriculture-Food-Environment (HAFEN) concept. The aim is to better understand the potential impact of the implementation of this concept in food consumption and production systems in terms of research needs. The paper suggests a research agenda dedicated to the modes of social and economic organization of key stakeholders in the implementation of Nexus-based systems, facilitating the convergence among health, food and environmental objectives. Based on a literature survey, three main topics are discussed: a) processes and drivers of change of food consumption practices; b) co-ordination and multi-agent governance modes to better account for health issues in agrifood systems; c) the analysis of paradigms that put forward health as an entry point to reshape existing agricultural and food systems, and associated modes of knowledge production. For each of these topics, we suggest a selection of research priorities for the future and conclude with methodological perspectives on the HAFEN

Designing normative open virtual enterprises

This is an Accepted Manuscript of an article published by Taylor & Francis Group in Enterprise Information Systems on 23/03/2016, available online: http://www.tandfonline.com/10.1080/17517575.2015.1036927.[EN] There is an increasing interest on developing virtual enterprises in order to deal with the globalisation of the economy, the rapid growth of information technologies and the increase of competitiveness. In this paper we deal with the development of normative open virtual enterprises (NOVEs). They are systems with a global objective that are composed of a set of heterogeneous entities and enterprises that exchange services following a specific normative context. In order to analyse and design systems of this kind the multi-agent paradigm seems suitable because it offers a specific solution for supporting the social and contractual relationships between enterprises and for formalising their business processes. This paper presents how the Regulated Open Multiagent systems (ROMAS) methodology, an agent-oriented software methodology, can be used to analyse and design NOVEs. ROMAS offers a complete development process that allows identifying and formalising of the structure of NOVEs, their normative context and the interactions among their members. The use of ROMAS is exemplified by means of a case study that represents an automotive supply chain.This work was partially supported by the projects [PROMETEOII/2013/019], [TIN2012-36586-C03-01], [FP7-29493], [TIN2011-27652-C03-00] and [CSD2007-00022], and the CASES project within the 7th European Community Framework Programme [grant agreement number 294931].Garcia Marques, ME.; Giret Boggino, AS.; Botti Navarro, VJ. (2016). Designing normative open virtual enterprises. Enterprise Information Systems. 10(3):303-324. https://doi.org/10.1080/17517575.2015.1036927S303324103Cardoso, H. L., Urbano, J., Brandão, P., Rocha, A. P., & Oliveira, E. (2012). ANTE: Agreement Negotiation in Normative and Trust-Enabled Environments. Advances on Practical Applications of Agents and Multi-Agent Systems, 261-264. doi:10.1007/978-3-642-28786-2_33Chu, X. N., Tso, S. K., Zhang, W. J., & Li, Q. (2002). Partnership Synthesis for Virtual Enterprises. The International Journal of Advanced Manufacturing Technology, 19(5), 384-391. doi:10.1007/s001700200028Davidsson, P., & Jacobsson, A. (s. f.). Towards Norm-Governed Behavior in Virtual Enterprises. Studies in Computational Intelligence, 35-55. doi:10.1007/978-3-540-88071-4_3DeLoach, S. A., & Ojeda, J. C. G. (2010). O-MaSE: a customisable approach to designing and building complex, adaptive multi-agent systems. International Journal of Agent-Oriented Software Engineering, 4(3), 244. doi:10.1504/ijaose.2010.036984DI MARZO SERUGENDO, G., GLEIZES, M.-P., & KARAGEORGOS, A. (2005). Self-organization in multi-agent systems. The Knowledge Engineering Review, 20(2), 165-189. doi:10.1017/s0269888905000494Dignum, V. 2003. “A Model for Organizational Interaction: Based on Agents, Founded in Logic.” PhD diss., Utrecht University.Dignum, V., and F. Dignum. 2006.A Landscape of Agent Systems for the Real World. Technical Report 44-CS-2006-061. Utrecht: Institute of Information and Computing Sciences, Utrecht University.Dignum, V., Meyer, J.-J. C., Dignum, F., & Weigand, H. (2003). Formal Specification of Interaction in Agent Societies. Lecture Notes in Computer Science, 37-52. doi:10.1007/978-3-540-45133-4_4Garcia, E. 2013. “Engineering Regulated Open Multiagent Systems.” PhD diss., Universitat Politecnica de Valencia.Garcia, E., Giret, A., & Botti, V. (s. f.). Software Engineering for Service-Oriented MAS. Lecture Notes in Computer Science, 86-100. doi:10.1007/978-3-540-85834-8_9Garcia, E., Giret, A., & Botti, V. (2013). A Model-Driven CASE tool for developing and verifying regulated open MAS. Science of Computer Programming, 78(6), 695-704. doi:10.1016/j.scico.2011.10.009Garcia, E., Giret, A., & Botti, V. (2011). Evaluating software engineering techniques for developing complex systems with multiagent approaches. Information and Software Technology, 53(5), 494-506. doi:10.1016/j.infsof.2010.12.012Garcia, E., Giret, A., & Botti, V. (2011). Regulated Open Multi-Agent Systems Based on Contracts. Information Systems Development, 243-255. doi:10.1007/978-1-4419-9790-6_20Garcia, E., Giret, A., & Botti, V. (2014). ROMAS Methodology. Handbook on Agent-Oriented Design Processes, 331-369. doi:10.1007/978-3-642-39975-6_11Hollander, C. D., & Wu, A. S. (2011). The Current State of Normative Agent-Based Systems. Journal of Artificial Societies and Social Simulation, 14(2). doi:10.18564/jasss.1750HORLING, B., & LESSER, V. (2004). A survey of multi-agent organizational paradigms. The Knowledge Engineering Review, 19(4), 281-316. doi:10.1017/s0269888905000317Julian, V., Rebollo, M., Argente, E., Botti, V., Carrascosa, C., & Giret, A. (2009). Using THOMAS for Service Oriented Open MAS. Lecture Notes in Computer Science, 56-70. doi:10.1007/978-3-642-10739-9_5Luck, M., Barakat, L., Keppens, J., Mahmoud, S., Miles, S., Oren, N., … Taweel, A. (2011). Flexible Behaviour Regulation in Agent Based Systems. Lecture Notes in Computer Science, 99-113. doi:10.1007/978-3-642-22427-0_8Meneguzzi, F., Modgil, S., Oren, N., Miles, S., Luck, M., & Faci, N. (2012). Applying electronic contracting to the aerospace aftercare domain. Engineering Applications of Artificial Intelligence, 25(7), 1471-1487. doi:10.1016/j.engappai.2012.06.004Presley, A., Sarkis, J., Barnett, W., & Liles, D. (2001). International Journal of Flexible Manufacturing Systems, 13(2), 145-162. doi:10.1023/a:1011131417956Saeki, M., & Kaiya, H. (2008). Supporting the Elicitation of Requirements Compliant with Regulations. Active Flow and Combustion Control 2018, 228-242. doi:10.1007/978-3-540-69534-9_18Such, J. M., García-Fornes, A., Espinosa, A., & Bellver, J. (2013). Magentix2: A privacy-enhancing Agent Platform. Engineering Applications of Artificial Intelligence, 26(1), 96-109. doi:10.1016/j.engappai.2012.06.009Telang, P. R., & Singh, M. P. (2009). Enhancing Tropos with Commitments. Lecture Notes in Computer Science, 417-435. doi:10.1007/978-3-642-02463-4_22Wooldridgey, M., & Ciancarini, P. (2001). Agent-Oriented Software Engineering: The State of the Art. Lecture Notes in Computer Science, 1-28. doi:10.1007/3-540-44564-1_

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