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_

The engineering of emergence in complex adaptive systems

Agent-oriented software engineering is a new software engineering paradigm that is ideally suited to the analysis and design of complex systems. Open distributed environments place a growing demand on complex systems to be adaptive as well. Complex systems that can learn from and adapt to dynamically changing environments are called complex adaptive systems. These systems are characterized by emergent behaviour caused by interactions between system components and the environment. Agent-oriented software engineering methodologies attempt to control emergence during analysis and design by engineering the complex system in such a way that the correct emergent behaviour results during run-time. In a complex adaptive system however, emergent behaviour cannot be predicted during analysis and design, as it evolves only after implementation. By restricting emergent behaviour, as is done in most agent-oriented software engineering approaches, a complex system cannot be fully adaptive as well. We propose the BaBe methodology that will enable a complex system to be adaptive by learning from its environment and modifying its behaviour during run-time. This methodology adds a run-time emergence model consisting of distributed Bayesian behaviour networks to the agent-oriented software engineering lifecycle. These networks are initialised by the human software engineer during analysis and design and deployed by Bayesian agencies (also complex adaptive systems). The Bayesian agents are simple, and collectively they implement distributed Bayesian behaviour networks. These networks, being specialized Bayesian networks, enable the Bayesian agents to collectively mine relationships between emergent behaviours and the interactions that caused them to emerge, in order to adapt the behaviour of the system. The agents are organized into heterarchies of agencies, where each agency activates one or more component behaviour depending on the inference in the underlying Bayesian behaviour network. These agencies assist the human software engineer to bridge the gap between the implementation and the understanding of emergent behaviour in complex adaptive systems. Due to the simplicity of the agents and the minimal communication amongst them, they can be implemented using a commercially available component architecture. We describe a prototype implementation of the Bayesian agencies using Sun’s Enterprise JavaBeans™ component architecture.Thesis (PhD (Computer Science))--University of Pretoria, 2005.Computer Scienceunrestricte

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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Organization of Multi-Agent Systems: An Overview

In complex, open, and heterogeneous environments, agents must be able to reorganize towards the most appropriate organizations to adapt unpredictable environment changes within Multi-Agent Systems (MAS). Types of reorganization can be seen from two different levels. The individual agents level (micro-level) in which an agent changes its behaviors and interactions with other agents to adapt its local environment. And the organizational level (macro-level) in which the whole system changes it structure by adding or removing agents. This chapter is dedicated to overview different aspects of what is called MAS Organization including its motivations, paradigms, models, and techniques adopted for statically or dynamically organizing agents in MAS.Comment: 12 page

On Agent-Based Software Engineering

Agent-based computing represents an exciting new synthesis both for Artificial Intelligence (AI) and, more generally, Computer Science. It has the potential to significantly improve the theory and the practice of modeling, designing, and implementing computer systems. Yet, to date, there has been little systematic analysis of what makes the agent-based approach such an appealing and powerful computational model. Moreover, even less effort has been devoted to discussing the inherent disadvantages that stem from adopting an agent-oriented view. Here both sets of issues are explored. The standpoint of this analysis is the role of agent-based software in solving complex, real-world problems. In particular, it will be argued that the development of robust and scalable software systems requires autonomous agents that can complete their objectives while situated in a dynamic and uncertain environment, that can engage in rich, high-level social interactions, and that can operate within flexible organisational structures

A survey of agent-oriented methodologies

This article introduces the current agent-oriented methodologies. It discusses what approaches have been followed (mainly extending existing object oriented and knowledge engineering methodologies), the suitability of these approaches for agent modelling, and some conclusions drawn from the survey

Organisational Abstractions for the Analysis and Design of Multi-Agent Systems

The architecture of a multi-agent system can naturally be viewed as a computational organisation. For this reason, we believe organisational abstractions should play a central role in the analysis and design of such systems. To this end, the concepts of agent roles and role models are increasingly being used to specify and design multi-agent systems. However, this is not the full picture. In this paper we introduce three additional organisational concepts - organisational rules, organisational structures, and organisational patterns - that we believe are necessary for the complete specification of computational organisations. We view the introduction of these concepts as a step towards a comprehensive methodology for agent-oriented systems

Analysis and design of multiagent systems using MAS-CommonKADS

This article proposes an agent-oriented methodology called MAS-CommonKADS and develops a case study. This methodology extends the knowledge engineering methodology CommonKADSwith techniquesfrom objectoriented and protocol engineering methodologies. The methodology consists of the development of seven models: Agent Model, that describes the characteristics of each agent; Task Model, that describes the tasks that the agents carry out; Expertise Model, that describes the knowledge needed by the agents to achieve their goals; Organisation Model, that describes the structural relationships between agents (software agents and/or human agents); Coordination Model, that describes the dynamic relationships between software agents; Communication Model, that describes the dynamic relationships between human agents and their respective personal assistant software agents; and Design Model, that refines the previous models and determines the most suitable agent architecture for each agent, and the requirements of the agent network