131,773 research outputs found

    Agent-oriented software engineering methodologies : analysis and future directions

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    The Internet of Things (IoT) facilitates in building cyber-physical systems, which are significant for Industry 4.0. Agent-based computing represents effective modeling, programming, and simulation paradigm to develop IoT systems. Agent concepts, techniques, methods, and tools are being used in evolving IoT systems. Over the last years, in particular, there has been an increasing number of agent approaches proposed along with an ever-growing interest in their various implementations. Yet a comprehensive and full-fledged agent approach for developing related projects is still lacking despite the presence of agent-oriented software engineering (AOSE) methodologies. One of the moves towards compensating for this issue is to compile various available methodologies, ones that are comparable to the evolution of the unified modeling language (UML) in the domain of object-oriented analysis and design. These have become de facto standards in software development. In line with this objective, the present research attempts to comprehend the relationship among seven main AOSE methodologies. More specifically, we intend to assess and compare these seven approaches by conducting a feature analysis through examining the advantages and limitations of each competing process, structural analysis, and a case study evaluation method. This effort is made to address the significant characteristics of AOSE approaches. The main objective of this study is to conduct a comprehensive analysis of selected AOSE methodologies and provide a proposal of a draft unified approach that drives strengths (best) of these methodologies towards advancement in this area.publishedVersio

    Evaluating how agent methodologies support the specification of the normative environment through the development process

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    [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. Journal of Computer Engineering Research, 1, 14–28.Argente, E., Botti, V., Carrascosa, C., Giret, A., Julian, V., & Rebollo, M. (2011). An abstract architecture for virtual organizations: The THOMAS approach. Knowledge and Information Systems, 29(2), 379–403.Argente, E., Botti, V., & Julian, V. (2009). GORMAS: An organizational-oriented methodological guideline for open MAS. In Proceedings of AOSE’09 (pp. 440–449).Argente, E., Botti, V., & Julian, V. (2009). Organizational-oriented methodological guidelines for designing virtual organizations. In Distributed computing, artificial intelligence, bioinformatics, soft computing, and ambient assisted living. Lecture Notes in Computer Science (Vol. 5518, pp. 154–162).Boella, G., Pigozzi, G., & van der Torre, L. (2009). Normative systems in computer science—Ten guidelines for normative multiagent systems. In G. Boella, P. Noriega, G. Pigozzi, & H. 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). Hingham, MA: Kluwer Academic Publishers.Botti, V., Garrido, A., Giret, A., & Noriega, P. (2011). The role of MAS as a decision support tool in a water-rights market. In Post-proceedings workshops AAMAS2011 (Vol. 7068, pp. 35–49). Berlin: Springer.Breaux, T. (2009). Exercising due diligence in legal requirements acquisition: A tool-supported, frame-based approach. In Proceedings of the IEEE international requirements engineering conference (pp. 225–230).Breaux, T. D., & Baumer, D. L. (2011). Legally reasonable security requirements: A 10-year ftc retrospective. Computers and Security, 30(4), 178–193.Breaux, T. D., Vail, M. W., & Anton, A. I. (2006). Towards regulatory compliance: Extracting rights and obligations to align requirements with regulations. In Proceedings of the 14th IEEE international requirements engineering conference, RE ’06 (pp. 46–55). Washington, DC: IEEE Computer Society.Bresciani, 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.Cardoso, H. L., & Oliveira, E. (2008). A contract model for electronic institutions. In COIN’07: Proceedings of the 2007 international conference on Coordination, organizations, institutions, and norms in agent systems III (pp. 27–40).Castor, A., Pinto, R. C., Silva, C. T. L. L., & Castro, J. (2004). Towards requirement traceability in tropos. In WER (pp. 189–200).Chopra, A., Dalpiaz, F., Giorgini, P., & Mylopoulos, J. (2009). Modeling and reasoning about service-oriented applications via goals and commitments. ICST conference on digital business.Cliffe, O., Vos, M., & Padget, J. (2006). Specifying and analysing agent-based social institutions using answer set programming. In O. Boissier, J. Padget, V. Dignum, G. Lindemann, E. Matson, S. Ossowski, J. Sichman, & J. Vázquez-Salceda (Eds.), Coordination, organizations, institutions, and norms in multi-agent systems. Lecture Notes in Computer Science (Vol. 3913, pp. 99–113). Springer. Berlin.Criado, N., Argente, E., Garrido, A., Gimeno, J. A., Igual, F., Botti, V., Noriega, P., & Giret, A. (2011). Norm enforceability in Electronic Institutions? In Coordination, organizations, institutions, and norms in agent systems VI (Vol. 6541, pp. 250–267). Springer.Dellarocas, C., & Klein, M. (2001). Contractual agent societies. In R. Conte & C. Dellarocas (Eds.), Social order in multiagent systems (Vol. 2, pp. 113–133)., Multiagent Systems, Artificial Societies, and Simulated Organizations New York: Springer.DeLoach, S. A. (2008). Developing a multiagent conference management system using the o-mase process framework. In Proceedings of the international conference on agent-oriented software engineering VIII (pp. 168–181).DeLoach, S. A., & Garcia-Ojeda, J. C. (2010). O-mase; a customisable approach to designing and building complex, adaptive multi-agent systems. 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Lecture Notes in Computer Science (Vol. 3346, pp. 181–198). Berlin: Springer.d’Inverno, M., Luck, M., Noriega, P., Rodriguez-Aguilar, J., & Sierra, C. (2012). Communicating open systems, 186, 38–94.Elsenbroich, C., & Gilbert, N. (2014). Agent-based modelling. In Modelling norms (pp. 65–84). Dordrecht: Springer.Esteva, M., Rosell, B., Rodriguez, J. A., & Arcos, J. L. (2004). AMELI: An agent-based middleware for electronic institutions. In AAMAS04 (pp. 236–243).Fenech, S., Pace, G. J., & Schneider, G. (2009). Automatic conflict detection on contracts. In Proceedings of the 6th international colloquium on theoretical aspects of computing, ICTAC ’09 (pp. 200–214).Garbay, C., Badeig, F., & Caelen, J. (2012). Normative multi-agent approach to support collaborative work in distributed tangible environments. In Proceedings of the ACM 2012 conference on computer supported cooperative work companion, CSCW ’12 (pp. 83–86). New York, NY: ACM.Garcia, E., Giret, A., & Botti, V. (2011). Regulated open multi-agent systems based on contracts. In Information Systems Development (pp. 243–255).Garcia, E., Tyson, G., Miles, S., Luck, M., Taweel, A., Staa, T. V., & Delaney, B. (2012). An analysis of agent-oriented engineering of e-health systems. In 13th international eorkshop on sgent-oriented software engineering (AOSE-AAMAS).Garcia, E., Tyson, G., Miles, S., Luck, M., Taweel, A., Staa, T. V., and Delaney, B. (2013). Analysing the Suitability of Multiagent Methodologies for e-Health Systems. In Agent-Oriented Software Engineering XIII, volume 7852, pages 134–150. Springer-Verlag.Garrido, A., Giret, A., Botti, V., & Noriega, P. (2013). mWater, a case study for modeling virtual markets. In New perspectives on agreement technologies (Vol. Law, Gover, pp. 563–579). Springer.Gteau, B., Boissier, O., & Khadraoui, D. (2006). Multi-agent-based support for electronic contracting in virtual enterprises. IFAC Symposium on Information Control Problems in Manufacturing (INCOM), 150(3), 73–91.Hollander, C. D., & Wu, A. S. (2011). The current state of normative agent-based systems. Journal of Artificial Societies and Social Simulation, 14(2), 6.Hsieh, F.-S. (2005). Automated negotiation based on contract net and petri net. In E-commerce and web technologies. Lecture Notes in Computer Science (Vol. 3590, pp. 148–157).Kollingbaum, M., Jureta, I. J., Vasconcelos, W., & Sycara, K. (2008). Automated requirements-driven definition of norms for the regulation of behavior in multi-agent systems. In Proceedings of the AISB 2008 workshop on behaviour regulation in multi-agent systems, Aberdeen, Scotland, U.K., April 2008.Li, T., Balke, T., Vos, M., Satoh, K., & Padget, J. (2013). Detecting conflicts in legal systems. In Y. Motomura, A. Butler, & D. Bekki (Eds.), New Frontiers in Artificial Intelligence (Vol. 7856, pp. 174–189)., Lecture Notes in Computer Science Berlin Heidelberg: Springer.Lomuscio, A., Qu, H., & Solanki, M. (2010) Towards verifying contract regulated service composition. Journal of Autonomous Agents and Multi-Agent Systems (pp. 1–29).Lopez, F., Luck, M., & d’Inverno, M. (2006). A normative framework for agent-based systems. Computational and Mathematical Organization Theory, 12, 227–250.Lpez, F. y, Luck, M., & dInverno, M. (2006). A normative framework for agent-based systems. Computational and Mathematical Organization Theory, 12(2–3), 227–250.Mader, P., & Egyed, A. (2012). Assessing the effect of requirements traceability for software maintenance. In 28th IEEE International Conference on Software Maintenance (ICSM) (pp. 171–180), Sept 2012.Mao, X., & Yu, E. (2005). Organizational and social concepts in agent oriented software engineering. In AOSE IV. Lecture Notes in Artificial Intelligence (Vol. 3382, pp. 184–202).Meyer, J.-J. C., & Wieringa, R. J. (Eds.). (1993). Deontic logic in computer science: Normative system specification. Chichester, UK: Wiley.Okouya, D., & Dignum, V. (2008). Operetta: A prototype tool for the design, analysis and development of multi-agent organizations (demo paper). In AAMAS (pp. 1667–1678).Malone, T. W., Smith J. B., & Olson, G. M. (2001). Coordination theory and collaboration technology. Mahwah, NJ: Lawrence Erlbaum Associates.Oren, N., Panagiotidi, S., Vázquez-Salceda, J., Modgil, S., Luck, M., & Miles, S. (2009). Towards a formalisation of electronic contracting environments. COIN (pp. 156–171).Osman, N., Robertson, D., & Walton, C. (2006). Run-time model checking of interaction and deontic models for multi-agent systems. In AAMAS ’06: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (pp. 238–240). 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    Multi-agent systems and security requirements analysis

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    Agent Oriented Software Engineering (AOSE) is a software paradigm that has grasped the attention of researchers the last few years. As a result, many different methods have been introduced to help developers in the development of multi-agent systems. However, so far, these methods have mainly neglected security requirements. The common approach towards the inclusion of security within a system is to identify security requirements after the definition of the system. However, this approach has provoked the emergence of computer systems afflicted with security vulnerabilities. In this paper we propose an analysis, based on the measures of criticality (how critical an actor of the system is) and complexity (represents the effort required by the actors of the system to achieve the requirements that have been imposed to them), which aims to identify possible bottlenecks of a multi-agent system with respect to security. An integrated agent-based health and social care information system is used as a case study throughout this paper

    A Constraint-based approach for modeling secure multiagent systems

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    Security plays an important role in the development of multiagent systems. However, a careful analysis of software development processes shows that the definition of security requirements is, usually, considered after the design of the system. This is, mainly, due to the fact that agent oriented software engineering methodologies have not integrated security concerns throughout their developing stages. The integration of security concerns during the whole range of the development stages could help towards the development of more secure multiagent systems. In this paper we introduce a constraint-based approach that extends the Tropos methodology in order to model security concerns throughout the whole development process. A description of the new concepts is given along with a security oriented process that integrates these concepts in Tropos

    Intelligence by Design: Principles of Modularity and Coordination for Engineerin

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    All intelligence relies on search --- for example, the search for an intelligent agent's next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the primary source of bias is engineering. This dissertation describes an approach, Behavior-Oriented Design (BOD) for engineering complex agents. A complex agent is one that must arbitrate between potentially conflicting goals or behaviors. Behavior-oriented design builds on work in behavior-based and hybrid architectures for agents, and the object oriented approach to software engineering. The primary contributions of this dissertation are: 1.The BOD architecture: a modular architecture with each module providing specialized representations to facilitate learning. This includes one pre-specified module and representation for action selection or behavior arbitration. The specialized representation underlying BOD action selection is Parallel-rooted, Ordered, Slip-stack Hierarchical (POSH) reactive plans. 2.The BOD development process: an iterative process that alternately scales the agent's capabilities then optimizes the agent for simplicity, exploiting tradeoffs between the component representations. This ongoing process for controlling complexity not only provides bias for the behaving agent, but also facilitates its maintenance and extendibility. The secondary contributions of this dissertation include two implementations of POSH action selection, a procedure for identifying useful idioms in agent architectures and using them to distribute knowledge across agent paradigms, several examples of applying BOD idioms to established architectures, an analysis and comparison of the attributes and design trends of a large number of agent architectures, a comparison of biological (particularly mammalian) intelligence to artificial agent architectures, a novel model of primate transitive inference, and many other examples of BOD agents and BOD development

    Designing normative open virtual enterprises

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    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_

    Agent oriented AmI engineering

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    On Agent-Based Software Engineering

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    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

    Simulation of complex environments:the Fuzzy Cognitive Agent

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    The world is becoming increasingly competitive by the action of liberalised national and global markets. In parallel these markets have become increasingly complex making it difficult for participants to optimise their trading actions. In response, many differing computer simulation techniques have been investigated to develop either a deeper understanding of these evolving markets or to create effective system support tools. In this paper we report our efforts to develop a novel simulation platform using fuzzy cognitive agents (FCA). Our approach encapsulates fuzzy cognitive maps (FCM) generated on the Matlab Simulink platform within commercially available agent software. We firstly present our implementation of Matlab Simulink FCMs and then show how such FCMs can be integrated within a conceptual FCA architecture. Finally we report on our efforts to realise an FCA by the integration of a Matlab Simulink based FCM with the Jack Intelligent Agent Toolkit
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