Hostname: page-component-8448b6f56d-gtxcr Total loading time: 0 Render date: 2024-04-17T20:25:12.974Z Has data issue: false hasContentIssue false

Software engineering for self-organizing systems

Published online by Cambridge University Press:  03 September 2015

H. Van Dyke Parunak
Affiliation:
AxonConnected, 2322 Blue Stone Hills Drive, Suite 20, Harrisonburg, VA 22801 e-mail: van.parunak@axonconnected.com
Sven A. Brueckner
Affiliation:
AxonConnected, 2322 Blue Stone Hills Drive, Suite 20, Harrisonburg, VA 22801 e-mail: van.parunak@axonconnected.com

Abstract

Self-organizing software systems are an increasingly attractive approach to highly distributed, decentralized, dynamic applications. In some domains (such as the Internet), the interaction of originally independent systems yields a self-organizing system de facto, and engineers must take these characteristics into account to manage them. This review surveys current work in this field and outlines its main themes, identifies challenges for future research, and addresses the continuity between software engineering in general and techniques appropriate for self-organizing systems.

Type
Articles
Copyright
© Cambridge University Press, 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Albus, J. S. 1992. RCS: a reference model architecture for intelligent control. IEEE Computer 25(5), 5659.CrossRefGoogle Scholar
Albus, J. S. 1997. The NIST real-time control system (RCS): an approach to intelligent systems research. Journal of Experimental and Theoretical Artificial Intelligence 9(2–3), 157174.CrossRefGoogle Scholar
aliCE 2008. aliCE (agents, languages and infrastructures for complexity engineering) Home. http://alice.unibo.it/xwiki/bin/view/aliCE/.Google Scholar
Axtell, R. & Epstein, J. 1997. Distributed Computation of Economic Equilibria via Bilateral Exchange. Technical report, Brookings Institution.Google Scholar
Bachrach, J., Beal, J. & McLurkin, J. 2010. Composable continuous space programs for robotic swarms. Neural Computing and Applications 19(6), 825847.CrossRefGoogle Scholar
Baresi, L., Bencomo, N., Cukic, B., Gorla, A., Inverardi, P., Nier-strasz, O., Park, S., Smith, D., Vogel, T., de Lemos, R. & Andersson, J. 2010. Dagstuhl Group c: Process. http://www.dagstuhl.de/Materials/Files/10/10431/10431.SWM12.Slides.ppt.Google Scholar
Beal, J. 2010a. Functional blueprints: an approach to modularity in grown systems. In Proceedings of the Seventh International Conference on Swarm Intelligence (ANTS 2010).CrossRefGoogle Scholar
Beal, J. 2011. Software engineering for self-organizing systems. Personal Communication.Google Scholar
Beal, J. & Knight, T. F. Jr 2008. Analyzing composability in a sparse encoding model of memorization and association. In Proceedings of the Seventh IEEE International Conference on Development and Learning (ICDL 2008).CrossRefGoogle Scholar
Becker, B., Karsai, G., Mankovskii, S., Muoller, H., Pezze, M., Schaofer, W., Sousa, J. P., Tahvildari, L., Tamura, G., Villegas, N. M. & Wong, K. 2010. Dagstuhl Group a: Towards Practical Run-Time V&V (for self-adaptive systems). http://www.dagstuhl.de/Materials/Files/10/10431/10431.SWM10.Slides.ppt.Google Scholar
Binney, J. J., Dowrick, N. J., Fisher, A. J. & Newman, M. E. J. 1992. The Theory of Critical PhenomenaAn Introduction to the Renormalization Group. Clarendon Press.Google Scholar
Boella, G., Torre, L. v. d. & Verhagen, H. 2007. Dagstuhl Seminar Proceedings 07122: Normative Multi-agent Systems. LZI Host.Google Scholar
Bonabeau, E. 2002. Agent-based modeling: methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences 99(Suppl 3), 72807287.CrossRefGoogle ScholarPubMed
Bonabeau, E., Dorigo, M. & Theraulaz, G. 1999. Swarm Intelligence: From Natural to Artificial Systems (SFI Studies in the Sciences of Complexity). Oxford University Press.CrossRefGoogle Scholar
Bonabeau, E., Henaux, F., Guerin, S., Snyers, D., Kuntz, P. & Theraulaz, G. 1998. Routing in telecommunications networks with “smart” ant-like agents. In Proceedings of the Second International Workshop on Intelligent Agents for Telecommunications Applications (IATA98), Lecture Notes in AI, 1437, 60–71. Springer.CrossRefGoogle Scholar
Bongaerts, L. 1998. Integration of Scheduling and Control in Holonic Manufacturing Systems. PhD thesis, PMA.Google Scholar
Booker, L. 2003. Learning tactics for swarming entities. In Swarming : Network Enabled C4ISR, Inbody, D., Chartier, C., DiPippa, D. & McDonald, B. (eds), 40–48. ASD C3I.Google Scholar
Brazier, F. M. T., Kephart, J. O., Parunak, H.V.D. & Huhns, M. N. 2009. Agents and service-oriented computing for autonomic computing: a research agenda. IEEE Internet Computing 13, 8287.CrossRefGoogle Scholar
Brooks, R. A. 1991. Intelligence without representation. Artificial Intelligence 47, 139159.CrossRefGoogle Scholar
Brueckner, S. 2000. Return from the Ant: Synthetic Ecosystems for Manufacturing Control. Dr.rer.nat.thesis.Google Scholar
Brueckner, S., Downs, E., Hilscher, R. & Yinger, A. 2008. Self-organizing integration of competing reasoners for information matching. In ECOSOA Workshop at SASO 2008.CrossRefGoogle Scholar
Brueckner, S., Hassas, S., Jelasity, M. & Yamins, D. 2007. Engineering Self-Organising Systems. Lecture Notes in AI 3910. Springer.CrossRefGoogle Scholar
Brueckner, S. & Parunak, H. V. D. 2003. Resource-aware exploration of emergent dynamics of simulated systems. In Autonomous Agents and Multi-Agent Systems (AAMAS 2003), Rosenschein, J. S., Wooldridge, M., Sandholm, T. & Yokoo, M. (eds), ACM, 781788.Google Scholar
Brueckner, S. & Parunak, H. V. D. 2005. Information-driven phase changes in multi-agent coordination. In Workshop on Engineering Self-Organizing Systems (ESOA, at AAMAS 2005), Lecture Notes in AI 3464, Brueckner, S. A., Di Marzo Serugendo, G., Karageorgos, A. & Nagpal, R. (eds). Springer.Google Scholar
Brueckner, S. A., Di Marzo Serugendo, G. & Hales, D. 2006. Engineering Self-Organising Systems. Lecture Notes in AI 3910. Springer.Google Scholar
Brueckner, S. A., Di Marzo Serugendo, G., Karageorgos, A. & Nagpal, R. 2005. Engineering Self-Organising Systems. Lecture Notes in Computer Science. Springer.Google Scholar
Brun, Y., Di Marzo Serugendo, G., Gqacek, C., Giese, H., Kienle, H., Litoiu, M., Mller, H., Pezz, M. & Shaw, M. 2009. Engineering self-adaptive systems through feedback loops. In Software Engineering for Self-Adaptive Systems, Cheng, B. H. C., de Lemos, R., Giese, H., Inverardi, P. & Magee, J. (eds), 5525Springer, 128145.Google Scholar
Camazine, S., Deneubourg, J.-L., Franks, N. R., Sneyd, J., Theraulaz, G. & Bonabeau, E. 2001. Self-Organization in Biological Systems. Princeton University Press.Google Scholar
Casadei, M., Viroli, M. & Gardelli, L. 2009. On the collective sort problem for distributed tuple spaces. Science of Computer Programming 74(9), 702722.CrossRefGoogle Scholar
Cheng, S.-W., Poladian, V. V., Garlan, D. & Schmerl, B. 2009. Improving architecture-based self-adaptation through resource prediction. In Software Engineering for Self-Adaptive Systems, Cheng, B. H. C., de Lemos, R., Giese, H., Inverardi, P. & Magee, J. (eds), 5525, Springer, 128145.CrossRefGoogle Scholar
Cicirello, V. A. & Smith, S. F. 2004. Wasp-like agents for distributed factory coordination. Journal of Autonomous Agents and Multi-Agent Systems 8, 237266.CrossRefGoogle Scholar
Clearwater, S. H. 1996. Market-Based Control: A Paradigm for Distributed Resource Allocation. World Scientific.CrossRefGoogle Scholar
Coore, D. 1999. Botanical Computing: A Developmental Approach to Generating Interconnect Topologies on an Amorphous Computer. PhD thesis.Google Scholar
Dawkins, R. 1976. The Selfish Gene. Oxford University Press.Google Scholar
de Lemos, R., Giese, H., Muoller, H. & Shaw, M. 2012. Software Engineering for Self -Adaptive Systems II, Lecture Notes in Computer Science 7475. Springer.Google Scholar
De Wolf, T. & Holvoet, T. 2005. Towards a methodology for engineering self-organising emergent systems. In The 2005 Conference on Self-Organization and Autonomic Informatics, Czap, H., Unland, R., Branki, C. & Tianfield, H. (eds), 18–34. IOS Press.Google Scholar
De Wolf, T. & Holvoet, T. 2007. Design patterns for decentralised coordination in self-organising emergent systems. In The Fourth International Workshop on Engineering Self-Organising Applications (ESOA) at AAMAS 2006, Brueckner, S., Hassas, S., Jelasity, M. and Yamins, D. (eds), LNAI 4335, 28–49. Springer.CrossRefGoogle Scholar
De Wolf, T., Holvoet, T. & Samaey, G. 2005. Engineering self-organising emergent systems with simulation-based scientific analysis. In The Fourth International Workshop on Engineering Self-Organising Applications, 146–160.Google Scholar
Denzinger, J. & Fuchs, D. 1999. Cooperation of heterogeneous provers. In The 16th International Joint Conference on Artificial Intelligence (IJCAI 1999), Dean, T. (ed.), 1, 10–15. Morgan Kaufmann.Google Scholar
Denzinger, J., Fuchs, M. & Fuchs, M. 1997. High performance ATP systems by combining several AI methods. In IJCAI-97, Pollack, M.E. (ed.), 102–107. Morgan Kaufmann.Google Scholar
Denzinger, J., Kasinger, H. & Bauer, B. 2011. Software engineering for self-organizing systems. Personal Communication.Google Scholar
Di Marzo Serugendo, G. 2009. Robustness and dependability of self-organising systems—a safety engineering perspective. In The 11th International Symposium on Stabilization, Safety and Security of Distributed Systems (SSS 2009), Guerraoui, R. and Petit, F. (eds), LNCS 5873, 254–268. Springer.CrossRefGoogle Scholar
Di Marzo Serugendo, G., Fitzgerald, J. & Romanovsky, A. 2010. Metaself—an architecture and development method for dependable self-* systems. In The 25th Symposium on Applied Computing (SAC 2010).CrossRefGoogle Scholar
Di Marzo Serugendo, G., Karageorgos, A., Rana, O. F. & Zambonelli, F. 2004. Engineering Self-Organising Systems, Lecture Notes in AI 2977. Springer.Google Scholar
Dötsch, F., Denzinger, J., Kasinger, H. & Bauer, B. 2010. Decentralized real-time control of water distribution networks using self-organizing multi-agent systems. In The 4th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2010), Gupta, I., Hassas, S. & Rolia, J. (eds), 223–232. IEEE.CrossRefGoogle Scholar
Doursat, R. 2006. The growing canvas of biological development: multiscale pattern generation on an expanding lattice of gene regulatory networks. InterJournal: Complex Systems, http://www.interjournal.org.Google Scholar
Edmonds, B. & Bryson, J. J. 2004. The insufficiency of formal design methods: the necessity of an experimental approach for the understanding and control of complex MAS. In The 3rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2004), Jennings, N. R., Tambe, M., Sierra, C. & Sonenberg, L. (eds), 938–945. IEEE.Google Scholar
Egan, C. 2011. Awareness: self-awareness in autonomic systems. http://www. aware-project.eu/.Google Scholar
Epstein, J. M. 2006. Generative Social Science, Princeton Studies in Complexity. Princeton University Press.Google Scholar
Flacher, F. & Sigaud, O. 2002. Spatial coordination through social potential fields and genetic algorithms. In The Seventh International Conference on Simulation of Adaptive Behavior (From Animals to Animats), Hallam, B., Floreano, D., Hallam, J., Meyer, J.-A. & Hayes, G. (eds), MIT Press.CrossRefGoogle Scholar
Gardelli, L., Viroli, M. & Omicini, A. 2007. Design patterns for self-organizing multiagent systems. In The 5th International Central and Eastern European Conference on Multi-Agent Systems (CEEMAS 2007), Hans-Dieter, B., Gabriela, L., Rineke, V., & Lszl Zsolt, V. (eds), LNCS 4696, 123–132. Springer.CrossRefGoogle Scholar
Georgas, J. C. & Taylor, R. N. 2009. Policy-based architectural adaptation management: robotics domain case studies. In Software Engineering for Self-Adaptive Systems, Cheng, B. H. C., de Lemos, R., Giese, H., Inverardi, P. & Magee, J. (eds), 5525 Springer, 89108.CrossRefGoogle Scholar
Georgiadis, I., Magee, J. & Kramer, J. 2002. Self-organising software architectures for distributed systems. In The First Workshop on Self-healing Systems (WOSS '02), Garlan, D., Kramer, J. & Wolf, A. (eds). ACM.CrossRefGoogle Scholar
Gershenson, C. 2007. Design and Control of Self-organizing Systems. PhD thesis.Google Scholar
Gershenson, C. & Heylighen, F. 2003. When Can We Call a System Self-Organizing? http://arxiv.org/pdf/nlin.AO/0303020.CrossRefGoogle Scholar
Glad, A., Buffet, O., Simonin, O. & Charpillet, F. 2009. Self-organization of patrolling-ant algorithms. In The International Conference on Self-Adaptive and Self-Organizing Systems (SASO09), 61–70.Google Scholar
Glad, A., Buffet, O., Simonin, O. & Charpillet, F. 2010. Influence of different execution models on patrolling ant behaviors: from agents to robots. In The Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS’10), 1173–1180.Google Scholar
Glad, A., Simonin, O., Buffet, O. & Charpillet, F. 2008. Theoretical study of ant-based algorithms for multi-agent patrolling. In The Eighteenth European Conference on Artificial Intelligence (ECAI’08), 626–630.Google Scholar
Grassé, P.-P. 1959. La reconstruction du nid et les coordinations inter-individuelles chez bellicositermes natalensis et cubitermes sp. la theorie de la stigmergie: essai d’interpretation du comportement des termites constructeurs. Insectes Sociaux 6, 4184.CrossRefGoogle Scholar
Guerin, S. & Kunkle, D. 2004. Emergence of constraint in self-organizing systems. Nonlinear Dynamics, Psychology, and Life Sciences 8(2), 131146.Google ScholarPubMed
Haddadi, A. & Sundermeyer, K. 1996. Belief-desire-intention agent architectures. In Foundations of Distributed Artificial Intelligence, O’Hare, G. M. P. & Jennings, N. R. (eds). John Wiley, 169185.Google Scholar
Hamdi, A., Antoine, V., Monmarché, N., Alimi, A. & Slimane, M. 2010. Artificial ants for automatic classification. In Artificial Ants: From Collective Intelligence to Real-life Optimization and Beyond, Monmarch, N., Guinand, F. & Siarry, P. (eds). John Wiley and Sons, 265290.Google Scholar
Handl, J., Knowles, J. & Dorigo, M. 2003. Ant-Based Clustering: A Comparative Study of its Relative Performance with Respect to k-means, Average Link and 1d-som. Technical Report TR-IRIDIA-2003-24, IRIDIA.Google Scholar
Heaven, W., Sykes, D., Magee, J. & Kramer, J. 2009. A case study in goal-driven architectural adaptation. In Software Engineering for Self-Adaptive Systems, Cheng, B. H. C., de Lemos, R., Giese, H., Inverardi, P. & Magee, J. (eds), 5525 Springer, 109127.CrossRefGoogle Scholar
Heusse, M., Guerin, S., Snyers, D. & Kuntz, P. 1998. Adaptive agent-driven routing and load balancing in communication networks. Advances in Complex Systems 1, 234257.CrossRefGoogle Scholar
Holvoet, T., Weyns, D. & Valckenaers, P. 2010. Delegate MAS patterns for large-scale distributed coordination and control applications. In EuroPlop.Google Scholar
Holzer, R., de Meer, H. & Bettstetter, C. 2008. On autonomy and emergence in self-organizing systems. In Intern. Workshop on Self-Organizing Systems (IWSOS), LNCS 5343. Springer.Google Scholar
Höning, N. 2011. Comments on Software Engineering for Self-Organizing Systems. Personal Communication.Google Scholar
Höning, N. & La Poutre, H. 2010. Designing comprehensible self-organising systems. In The Fourth IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2010), 233–242. IEEE Computer Society.CrossRefGoogle Scholar
Huang, H.-M., Pavek, K., Novak, B., Albus, J. & Messina, E. 2005. A framework for autonomy levels for unmanned systems (ALFUS). In AUVSI Unmanned Systems 2005.Google Scholar
Hudson, J., Denzinger, J., Kasinger, H. & Bauer, B. 2010. Efficiency testing of self-adapting systems by learning of event sequences. In The 2nd International Conference on Adaptive and Self-adaptive Systems and Applications (ADAPTIVE 2010), 200–205. IARIA.Google Scholar
IBM 2006. An architectural blueprint for autonomic computing. Technical report, IBM.Google Scholar
ITEA 2010. Agenda. In The Developing And Testing Autonomy (DATA) Workshop. International Test and Evaluation Association (ITEA).Google Scholar
Janssen, M. A. 2002. Complexity and Ecosystem Management: The Theory and Practice of Multi-Agent Systems. Edward Elgar.CrossRefGoogle Scholar
Kasinger, H., Bauer, B. & Denzinger, J. 2009. Design pattern for self-organizing emergent systems based on digital infochemicals. In EASe 2009, 45–55.Google Scholar
Kearns, M., Mansour, Y. & Ng, A. 1999. A sparse sampling algorithm for near-optimal planning in large markov decision processes. In The Sixteenth International Joint Conference on Artificial Intelligence, 1324–1331. Morgan Kaufmann.Google Scholar
Kephart, J. O. & Chase, D. M. 2003. The vision of autonomic computing. Computer 36(1), 4150.CrossRefGoogle Scholar
Kephart, J. O., Hogg, T. & Huberman, B. A. 1989. Dynamics of computational ecosystems. Physics Review 40A, 404421.CrossRefGoogle Scholar
Kinny, D., Georgeff, M. & Rao, A. 1996. A methodology and modelling technique for systems of BDI agents. In Agents Breaking Away. 7th European Workshop on Modelling Autonomous Agents in a Multi-Agent World (MAAMAW’96), Walter Vande, V. & John, W. P. (eds), Lecture Notes in Artificial Intelligence 1038, 56–71. Springer.CrossRefGoogle Scholar
Kocsis, L. & Szepesvári, C. 2006. Bandit based Monte-Carlo planning. In The EMCL 2006, Fiirnkranz, J., Scheffer, T. & Spiliopoulou, M. (eds), LNCS 4212. Springer, 282293.Google Scholar
Koestler, A. 1967. The Ghost in the Machine. Penguin Group.Google Scholar
Kuntz, P. & Layzell, P. 1997. An ant clustering algorithm applied to partitioning in VLSI technology. In Fourth European Conference on Artificial Life, Husbands, P. and Harvey, I. (eds), 417–424. MIT Press.Google Scholar
Larman, C. & Basili, V. 2003. Iterative and incremental development: a brief history. IEEE Computer 36(36), 211.CrossRefGoogle Scholar
Lejter, M. & Dean, T. 1996. A framework for the development of multiagent architectures. IEEE Expert 11, 4759.CrossRefGoogle Scholar
Lerman, K., Martinoli, A. & Galstyan, A. 2005. A review of probabilistic macroscopic models for swarm robotic systems. In Swarm Robotics Workshop: State-of-the-art Survey, Sahin, E. & Spears, W. (eds). Springer-Verlag, 143152.CrossRefGoogle Scholar
Mamei, M. & Zambonelli, F. 2005. Field-Based Coordination for Pervasive Multiagent Systems. Springer.Google Scholar
Masoud, S. A. & Masoud, A. A. 2000. Constrained motion control using vector potential fields. IEEE Trans. on Systems, Man, and Cybernetics 30(3), 251272.CrossRefGoogle Scholar
Maxwell, J. C. 1867. On governors. Proceedings of the Royal Society of London 16, 270283.Google Scholar
Merkle, D., Middendorf, M. & Scheidler, A. 2007. Swarm controlled emergence—designing an anti-clustering ant system. InIEEE Swarm Intelligence Symposium, 242249.Google Scholar
Monmarché, N. 1999. On data clustering with artificial ants. In AAAI-99 & GECCO-99 Workshop on Data Mining with Evolutionary Algorithms: Research Directions, Freitas, A. A. (eds), 2326. AAAI.Google Scholar
Nagpal, R. 2001. Programmable Self-Assembly: Constructing Global Shape using Biologically-inspired Local Interactions and Origami Mathematics. PhD thesis.Google Scholar
Newman, M. E. J. 2010. Networks: An Introduction. Oxford University Press.CrossRefGoogle Scholar
Nierstraz, O., Denker, M. & Renggli, L. 2009. Model-centric, context-aware software adaptation. In Software Engineering for Self-Adaptive Systems, Cheng, B. H. C., de Lemos, R., Giese, H., Inverardi, P. & Magee, J. (eds), 5525, Springer, 128145.CrossRefGoogle Scholar
Nii, H. P. 1986a. Blackboard systems. AI Magazine 7(3), 4053.Google Scholar
Nii, H. P. 1986b. Blackboard systems. AI Magazine 7(4), 82107.Google Scholar
Odell, J. J., Van Dyke Parunak, H., Brueckner, S. & Sauter, J. 2003. Temporal aspects of dynamic role assignment. In Workshop on Agent-Oriented Software Engineering (AOSE03) at AAMAS03, LNAI 2935, 201–213. Springer.CrossRefGoogle Scholar
OMG 2008. Software & Systems Process Engineering Meta-Model Specification. Technical report, Object Management Group. http://www.omg.org/spec/SPEM/2.0/PDF.Google Scholar
Omicini, A. 2002. Towards a notion of agent coordination context. In Process Coordination and Ubiquitous Computing, Marinescu, D. & Lee, C. (eds). CRC Press, 187200.Google Scholar
Omicini, A., Ricci, A., Viroli, M., Castelfranchi, C. & Tummolini, L. 2004. Coordination artifacts: environment-based coordination for intelligent agents. In 3rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2004), Jennings, N. R., Tambe, M., Sierra, C. & Sonenberg, L. (eds), 1, 286–293. ACM.Google Scholar
Omicini, A. & Zambonelli, F. 1999. Coordination for internet application development. Autonomous Agents and Multi-Agent Systems 23(3), 251269.CrossRefGoogle Scholar
Parunak, H. V. D. 1997. ‘go to the ant’: engineering principles from natural agent systems. Annals of Operations Research 75, 69101.CrossRefGoogle Scholar
Parunak, H. V. D. 2006. A survey of environments and mechanisms for human-human stigmergy. In Proceedings of E4MAS 2005, Weyns, D., Michel, F. & Van Dyke Parunak, H. (eds), LNAI 3830, Lecture Notes on AI, 163–186. Springer.CrossRefGoogle Scholar
Parunak, H. V. D., Belding, T. C. & Brueckner, S. A. 2008. Prediction horizons in agent models. In Engineering Environment-Mediated Multiagent Systems (Satellite Conference at ECCS 2007), Weyns, D., Brueckner, S. & Demazeau, Y. (eds), LNCS 5049, 88–102. Springer.CrossRefGoogle Scholar
Parunak, H. V. D. & Brueckner, S. 2001. Entropy and self-organization in multi-agent systems. In The Fifth International Conference on Autonomous Agents (Agents 2001), André, E., Sen, S., Frasson, C. & Müller, J. P. (eds), 124–130. ACM.Google Scholar
Parunak, H. V. D., Brueckner, S. & Savit, R. 2004. Universality in multi-agent systems. In Third International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2004), 930–937. ACM.Google Scholar
Parunak, H. V. D., Brueckner, S., Weyns, D., Holvoet, T. & Valckenaers, P. 2007. E pluribus unum: Polyagent and delegate mas architectures. In Eighth International Workshop on Multi-Agent-Based Simulation (MABS07), Lecture Notes in AI 5003, 36–51. Springer.CrossRefGoogle Scholar
Parunak, H. V. D. & Brueckner, S. A. 2004. Engineering swarming systems. In Methodologies and Software Engineering for Agent Systems, Bergenti, F., Gleizes, M.-P. & Zambonelli, F. (eds). Kluwer, 341376.CrossRefGoogle Scholar
Parunak, H. V. D., Rohwer, R., Belding, T. C. & Brueckner, S. 2006. Dynamic decentralized any-time hierarchical clustering. In Proceedings of the Fourth International Workshop on Engineering Self-Organizing Systems (ESOA’06), LNAI 4335. Springer.Google Scholar
Parunak, H. V. D., Ward, A. C., Fleischer, M. & Sauter, J. A. 1999. The RAPPID project: symbiosis between industrial requirements and mas research. Journal ofAutonomous Agents and Multi-Agent Systems 2(2), 111140.CrossRefGoogle Scholar
Payton, D., Daily, M., Estowski, R., Howard, M. & Lee, C. 2001. Pheromone robotics. Journal Autonomous Robots 11(3), 319324.CrossRefGoogle Scholar
Peeters, P., Van Brussel, H., Valckenaers, P., Wyns, J., Bongaerts, L., Kollingbaum, M. & Heikkila, T. 2001. Pheromone based emergent shop floor control system for flexible flow shops. Artificial Intelligence in Engineering 15, 343352.CrossRefGoogle Scholar
Prusinkiewicz, P. & Lindenmayer, A. 1990. The Algorithmic Beauty of Plants. Springer.CrossRefGoogle Scholar
Puviani, M., Di Marzo Serugendo, G., Frei, R. & Cabri, G. 2011. A method fragments approach to methodologies for engineering self-organising systems. ACM Transactions on Autonomous and Adaptive Systems 7(3), 125.CrossRefGoogle Scholar
Rao, A. S. & Georgeff, M. P. 1991. Modeling rational agents within a BDI architecture. In International Conference on Principles of Knowledge Representation and Reasoning (KR-91), Allen, J., Fikes, F., & Sandwall, E. (eds), 473–484. Morgan Kaufman.Google Scholar
Rice, H. G. 1953. Classes of recursively enumerable sets and their decision problems. Transactions of the American Mathematical Society 74, 358366.CrossRefGoogle Scholar
Ricketts, S. 1996. Holonic manufacturing systems.Google Scholar
Salehie, M. & Tahvildari, L. 2009. Self-adaptive software: landscape and research challenges. ACM Transactions on Autonomic and Autonomic Systems (TAAS) 4(2), 142.Google Scholar
SAPERE 2011. Eu SAPERE Project (Self-Aware Pervasive Service Ecosystems). http://www.sapere-project.eu/.Google Scholar
SASO 2011. Self-adaptive and Self-Organizing Systems. http://www.saso-conference.org/.Google Scholar
Sauter, J. A., Matthews, R., Parunak, H. V. D. & Brueckner, S. 2002. Evolving adaptive pheromone path planning mechanisms. In Autonomous Agents and Multi-Agent Systems (AAMAS02). ACM, 434440.Google Scholar
Sauter, J. A., Matthews, R., Parunak, H. V. D. & Brueckner, S. A. 2005. Performance of digital pheromones for swarming vehicle control. In Fourth International Joint Conference on Autonomous Agents and Multi-Agent Systems, Pechoucek, M., Steiner, D. & Thompson, S. (eds), 903–910. ACM.CrossRefGoogle Scholar
Sauter, J. A., Matthews, R., Parunak, H. V. D. & Brueckner, S. A. 2007. Effectiveness of digital pheromones controlling swarming vehicles in military scenarios. Journal of Aerospace Computing, Information, and Communication 4(5), 753769.CrossRefGoogle Scholar
Sauter, J. A., Matthews, R. S., Robinson, J. S., Moody, J. & Riddle, S. P. 2009. Swarming unmanned air and ground systems for surveillance and base protection. In AIAA Infotech@Aerospace 2009 Conference. AIAA.CrossRefGoogle Scholar
Savit, R., Brueckner, S. A., Parunak, H. V. D. & Sauter, J. 2002. Phase structure of resource allocation games. Physics Letters A 311, 359364.CrossRefGoogle Scholar
Scholtes, I. 2010. Harnessing Complex Structures and Collective Dynamics in Large Networked Computing Systems. PhD thesis.Google Scholar
Scholtes, I. 2011. Thoughts on Engineering Self-Organizing Systems. Personal Communication.Google Scholar
Scholtes, I., Botev, J., Hohfeld, A., Schloss, H. & Esch, M. 2008. Awareness-driven phase transitions in very large scale distributed systems. In The Second IEEE International Conferences on Self-Adaptive and Self-Organizing Systems (SASO), Brueckner, S. A., Robertson, P. & Bellur, U. (eds). IEEE.CrossRefGoogle Scholar
Sengers, P. 1999. Designing comprehensible agents. In Sixteenth International Joint Conference on Artificial Intelligence (IJCAI), Dean, T. (ed.), 1227–1232. Lawrence Erlbaum.Google Scholar
Shen, W. & Norrie, D. 1997. Facilitators, mediators or autonomous agents. In Second International Workshop on CSCW in Design, Siriruchatapong, P., Zongkai, L. and Barthes, J. P. (eds), 119–124. International Academic Pubilshers, Beijing.Google Scholar
Simon, H. A. 1969. The Sciences of the Artificial. MIT Press.Google Scholar
Simonin, O., Charpillet, F., Buffet, O. & Glad, A. 2011. Engineering Self-Organizing Systems. Personal Communication.Google Scholar
Spicher, A. & Michel, O. 2006. Declarative modeling of a neurulation-like process. BioSystems 87, 281288.CrossRefGoogle ScholarPubMed
T3 Group 2012. T3 Group: Trust Theory Technology. http://t3.istc.cnr.it/trustwiki/index.php/Main_Page.Google Scholar
Tyrrell, A., Auer, G. & Bettstetter, C. 2007. Biologically inspired synchronization for wireless networks. In Advances in Biologically Inspired Information Systems: Models, Methods, and Tools, Dressler, F. & Carreras, I. (eds), Studies in Computational Intelligence. Springer, 4762.CrossRefGoogle Scholar
Valckenaers, P. 2011. Self-Organizing Systems with Emergent Behavior. Personal Communication.Google Scholar
Valckenaers, P. & Van Brussel, H. 2005. Holonic manufacturing execution systems. CIRP Annals of Manufacturing Technology 54(1), 427432.CrossRefGoogle Scholar
Valckenaers, P., Van Brussel, H., Hadeli, K., Bochmann, O., Germain, B. S. & Zamfirescu, C. 2003. On the design of emergent systems: an investigation of integration and interoperability issues. Engineering Applications of Artificial Intelligence 16, 377393.CrossRefGoogle Scholar
Van Brussel, H., Wyns, J., Valckenaers, P., Bongaerts, L. & Peeters, P. 1998. Reference architecture for holonic manufacturing systems: prosa. Computers In Industry 37(3), 255276.CrossRefGoogle Scholar
Villatoro, D. 2011. Social Norms for Self-policing Multi-agent Systems and Virtual Societies. PhD thesis.Google Scholar
Viroli, M. & Casadei, M. 2009. Biochemical tuple spaces for self-organising coordination. In Coordination Languages and Models, Field, J. & Vasconcelos, V. T. (ed.), 5521, Springer, 143162.CrossRefGoogle Scholar
Viroli, M. & Omicini, A. 2011. The “self-organising coordination” Paradigm in the Software Engineering of SOS. Technical report, Universita di Bologna.Google Scholar
Viroli, M., Ricci, A., Zambonelli, F., Holvoet, T. & Schelfthout, K. 2007. Infrastructures for the environment of multiagent systems. Journal of Autonomous Agents and Multi-Agent Systems 14(1), 4960.CrossRefGoogle Scholar
Viroli, M. & Zambonelli, F. 2010. A biochemical approach to adaptive service ecosystems. Information Sciences 180(10), 18761892.CrossRefGoogle Scholar
Walsham, B. 2003. Simplified and Optimised Ant Sort for Complex Problems: Document Classification. Bachelor of Software Engineering thesis.Google Scholar
Watson, D. P. & Scheidt, D. H. 2005. Autonomous systems. Johns Hopkins APL Technical Digest 26(4), 368375.Google Scholar
Wegner, P. 1997. Why interaction is more powerful than algorithms. Communications ofthe ACM 40, 8191.CrossRefGoogle Scholar
Werfel, J. 2006. Anthills Built to Order: Automating Construction with Artificial Swarms. PhD thesis.Google Scholar
Weyns, D 2010. Architecture-Based Design of Multi-Agent Systems. Springer.CrossRefGoogle Scholar
Weyns, D. 2011. Software engineering for self-organizing systems. Personal Communication.Google Scholar
Weyns, D., Boucke, N. & Holvoet, T. 2008. A field-based versus a protocol-based approach for adaptive task assignment. Journal on Autonomous Agents and Multi-Agent Systems 17(2), 288319.CrossRefGoogle Scholar
Weyns, D., Malek, S., Andersson, J. & Schmerl, B. 2011. Call for Papers, Special Issue on “state of the art in self-adaptive software systems”, Journal of Systems and Software (jss). http://www.elsevierscitech.com/cfp/CFP-JSS-special-issue-2010.pdf.Google Scholar
Weyns, D., Schmerl, B., Grassi, V., Malek, S., Mirandola, R., Prehofer, C., Wuttke, J., Andersson, J., Giese, H. & Goschka, K. 2012. On patterns for decentralized control in self-adaptive systems. In Software Engineering for Self-Adaptive Systems II, de Lemos, R., Giese, H., Müller, H. & Shaw, M. (eds), LNCS 7475, pp. 76–107. Springer.Google Scholar
Wiener, N. 1948. Cybernetics. MIT Press.Google ScholarPubMed
Wooldridge, M. & Jennings, N. R. 1995. Agent theories, architectures, and languages: a survey. In Intelligent Agents, Wooldridge, M. & Jennings, N. R. (eds). Springer, 122.CrossRefGoogle Scholar