Skip to main content
SpringerLink
Log in

Complexity and Emergence in Engineering Systems

  • Chapter
Complex Systems in Knowledge-based Environments: Theory, Models and Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 168))

Abstract

The purpose of this chapter is to introduce the reader to the key concepts of complexity and emergence, and to give an overview of the state of the art techniques used to study and engineer systems to exhibit particular emergent properties. We include theories both from complex systems engineering and from the physical sciences. Unlike most reviews, which usually focus solely on one of these, we wish to analyse the ways in which they relate to one another, as well as how they differ, since there is often a lack of clarity on this.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Allavena, A., Demers, A., Hopcroft, J.: Correctness of gossip-based membership protocol. In: Proceedings of the 24th ACM Symposium on the Principle of Distributed Computing (2005)

    Google Scholar 

  2. Atkins, E.M., Abdelzhar, T.F., Shin, K.G., Durfee, E.H.: Planning and resource allocation for hard real-time, fault-tolerant plan execution. Autonomous Agents and Multi-Agent Systems Journal (Best of Agents 1999 special issue) (1–2), 57–78 (March/June 1999)

    Google Scholar 

  3. Balbo, F., Pinson, S.: Toward a multi-agent modelling approach for urban public transportation systems. In: Engineering societies in the agents world II. Springer, Heidelberg (2001)

    Google Scholar 

  4. Barbuceanu, M., Gray, T., Mankovski, S.: Coordinating with obligations. In: Proceedings of the second international conference on autonomous agents, pp. 62–69 (1998)

    Google Scholar 

  5. Bedau, M.A.: Downward causation and the autonomy of weak emergence. Principia 3, 5–50 (2003)

    Google Scholar 

  6. Beer, R.D.: Autopoiesis and cognition in the game of life. Artificial Life 10, 309–326 (2004)

    Article  Google Scholar 

  7. Benerecetti, M., Cimatti, A.: Symbolic model checking for multi-agent systems. In: Proceedings of the model checking and artificial intelligence workshop (MoChArt 2002), held with 15th ECAI, Lyon, France, pp. 1–8 (July 21–26, 2002)

    Google Scholar 

  8. Bennett, C.H.: On the nature and origin of complexity in discrete, homogenou, locally-ineracting systems. Found. Phys. 16, 585–592 (1986)

    Article  MathSciNet  Google Scholar 

  9. Boffetta, G., Cencini, M., Falcioni, M., Vulpiani, A.: Predictability: a way to characterise complexity. Physics Reports 356, 367–474 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  10. Bonabeau, E., Dessalles, J.L.: Detection and emergence. Intellectica 2(25), 85–94 (1997)

    Google Scholar 

  11. Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, Oxford (1999)

    MATH  Google Scholar 

  12. Bordini, R., Fisher, M., Visser, W., Wooldridge, M.: Verifying multi-agent programs by model-checking. Autonomous agents and multi-agent systems 12, 239–256 (2006)

    Article  Google Scholar 

  13. Borger, E., Stark, R.: Abatrsct State Machines: A method for high-level system design and analysis. Springer, Heidelberg (2003)

    Google Scholar 

  14. Cannata, N., Corradini, F., Merelli, E., Omicini, A., Ricci, A.: An agent-oriented conceptual framework for systems biology. Trans. On Comput. Syst. Biol. 3, 105–122 (2005)

    Article  Google Scholar 

  15. Capera, D., George, J.P., Glize, M.P.: The amas theory for complex problem solving based on self-organising cooperative agents. In: The First International TAPOCS Workshop at IEEE 12th WETICE, pp. 383–388 (2003)

    Google Scholar 

  16. Cardelli, L., Gordon, A.D.: Mobile ambients. In: Foundations of Software Science and Computation Structures: First Interational Conference FOSSACS 1998. Springer, Berlin (1998)

    Google Scholar 

  17. Chaitin, G.J.: On the length of programs for computing finite binary sequences. J. Assoc. Comput. Mach. 13, 547–569 (1966)

    MATH  MathSciNet  Google Scholar 

  18. Chen, C.-C., Nagl, S.B., Clack, C.D.: A calculus for multi-level emergent behaviours in component-based systems and simulations. In: Aziz-Alaoui, M.A., Bertelle, C., Cosaftis, M., Duchamp, G.H. (eds.) Proceedings of the satellite conference on Emergent Properties in Artificial and Natural Systems (EPNACS) (October 2007)

    Google Scholar 

  19. Chen, C.-C., Nagl, S.B., Clack, C.D.: A method for validating and discovering associations between multi-level emergent behaviours in agent-based simulations. In: Nguyen, N.T., Jo, G.S., Howlett, R.J., Jain, L.C. (eds.) KES-AMSTA 2008. LNCS (LNAI), vol. 4953. Springer, Heidelberg (2008)

    Google Scholar 

  20. Clarke, E.M., Grumberg, E.M., Peled, D.A.: Model Checking. MIT Press, Cambridge (2000)

    Google Scholar 

  21. Corradini, F., Merelli, E., Vita, M.: A multi-agent system for modelling carbohydrate oxidation in cell. In: Computational Science and Its Applications (ICCSA 2005: International Conference, Part II), Singapore, May 9-12, 2005, Proceedings, pp. 1264–1273 (May 2005)

    Google Scholar 

  22. Cotsaftis, M.: In: Aziz-Alaoui, M.A., Bertelle, C., Cotsaftis, M., Duchamp, G.H.E. (eds.) Proceedings of EPNACS 2007, Emergent Properties in Natural and Artificial Systems, Dresden, Germany, October 1–5, pp. 9–33 (2007)

    Google Scholar 

  23. Crutchfield, J.P.: The calculi of emergence: Computation, dynamics, and induction. Physica D 75, 11–54 (1994)

    Article  MATH  Google Scholar 

  24. Crutchfield, J.P., Feldman, D.P.: Regularities unseen, randomness observed: Levels of entropy convergence. Chaos 13(1), 25–54 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  25. Darley, V.: Emergent phenomena and complexity. Arificial Life 4, 411–416 (1994)

    Google Scholar 

  26. Demazeau, Y.: Steps towards multi-agent oriented programming. In: First International Workshop on Multi Agent Systems, Boston, Mass. (1997)

    Google Scholar 

  27. DeWolf, T., Holvoet, T.: A catalogue of decentralised coordination mechanisms for designing self-organising emergent applications. Technical Report CW 458, Department of Computer Science, K. U. Leuven (2006)

    Google Scholar 

  28. DeWolf, T., Holvoet, T.: Decentralised coordination mechanisms as design patterns for self-organising emergent applications. In: Proceedings of the Fourth International Workshop on Engineering Self-Organising Applications, pp. 40–61 (2006)

    Google Scholar 

  29. Dignum, F., Morley, D., Sonenberg, L., Cavedon, L.: Towards socially sophisticated bdi agents. In: Proceedings of ICMAS 2000 (2000)

    Google Scholar 

  30. d’Inverno, M., Luck, M.: Understanding agent systems, ch. 3, pp. 39–66. Springer, Heidelberg (2001)

    MATH  Google Scholar 

  31. Dowling, J., Cunningham, R., Curran, E., Cahill, V.: Component and system-wide self-* properties in decentralized distributed systems. In: Self-Star: Internatinal Workshop on Self*- Properties in Complex Information Systems (2004)

    Google Scholar 

  32. Eberhart, R.C., Shi, Y.: Particle swarm optimization: developments, applications and resources. In: Proceedings of the IEEE Congress on Evolutionary Computation, pp. 27–30 (2001)

    Google Scholar 

  33. Edmonds, B.: Engineering self-organising systems, methodologies and applications. In: Brueckner, S.A., Di Marzo Serugendo, G., Karageorgos, A., Nagpal, R. (eds.) ESOA 2005. LNCS (LNAI), vol. 3464. Springer, Heidelberg (2005)

    Google Scholar 

  34. Edmonds, B., Bryson, J.: The insufficiency of formal design methods - the necessity of an experimental approach - for the understanding and control of complex multi-agent systems. In: Proceedings of AAMAS, pp. 938–945 (2004)

    Google Scholar 

  35. Edmunds, B.: Syntactic measures of complexity. PhD thesis, University of Manchester (1999)

    Google Scholar 

  36. Esterline, A., Rorie, T.: Using the π-calculus to model multi-agent systems. In: Greenbelt, M.D. (ed.) Proceedings of the First International Workshop on Formal APproaches to Agent-Based Systems, vol. 1871. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  37. Eugster, P., Felber, P., Guerraoui, P., Kermarrec, A.: The many faces of publish/subscribe. ACM Computing Surveys 35(2), 114–131 (2003)

    Article  Google Scholar 

  38. Ferber, J.: Multi-Agents Systems: An Introduction to Distributed Artificial Intelligence. Addison-Wesley, Reading (1999)

    Google Scholar 

  39. Ferber, J., Gutknecht, O.: A meta-model for the analysis and design of organisations in multi-agent systems. In: Proceedings of the Third International Conference on Multi-Agent Systems (ICMAS 1998), pp. 128–135. IEEE Computer Society Press, Los Alamitos (1998)

    Chapter  Google Scholar 

  40. Ferber, J., Muller, J.-P.: Influences and reaction: A model of situated multiagent systems. In: Second international conference on multi-agent systems, AAAI (1996)

    Google Scholar 

  41. Freeman, E., Hupfer, S., Arnold, K.: JavaSpaces principles, patterns, and practice. Addison-Wesley, Reading (1999)

    Google Scholar 

  42. Gardelli, L., Viroli, M., Omicini, A.: Design patterns for self-organising multi-agent systems. In: Proceedings of EEDAS 2007 (2007)

    Google Scholar 

  43. George, J.P., Gleizes, M.P.: Experiments in emergent programming using self-organising multi-agent systems. In: Pěchouček, M., Petta, P., Varga, L.Z. (eds.) CEEMAS 2005. LNCS (LNAI), vol. 3690, pp. 450–459. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  44. Giavitto, J.-L., Michel, O.: Mgs - a rule-based programming language for complex objects and collections. Electronic Notes in Theoretical Computer Science, 59 (2001)

    Google Scholar 

  45. Gleizes, M.-P., Camps, V., George, J.-P., Capera, D.: Engineering systems which generate emergent functionalities. In: Engineering Environment-Mediated Multiagent Systems (EEMMAS 2007). LNCS. Springer, Heidelberg (2007)

    Google Scholar 

  46. Gmytrasiewicz, P.L., Durfee, E.H.: Rational coordination in multi-agent systems. Autonomous Agents and Multi-Agent Systems Journal 3(4), 319–350 (2000)

    Article  Google Scholar 

  47. Godel, K.: Uber formal unentscheidbare satze der principia mathematica und verwandter system i. Monatschefte Math. Phys. 38, 173–198

    Google Scholar 

  48. Goldberg, D.: Genetic Algorithms in Search Optimisation and Machine Learning. Addison-Wesley, Reading (1989)

    Google Scholar 

  49. Grassberger, P.: Toward a quantitative theory of self-generated complexity. International Journal of Theoretical Physics 25, 907–938 (1986)

    Article  MATH  MathSciNet  Google Scholar 

  50. Harel, D.: Statecharts - a visual formalism for complex systems. SCP 8, 231–274 (1987)

    MATH  MathSciNet  Google Scholar 

  51. Harel, D.: Algorithmics - The Spirit of Computing, 3rd edn. Addison-Wesley, Reading (2004)

    MATH  Google Scholar 

  52. Holland, J.: Adaptation in Natural and Artificial Systems. MIT Press, Cambridge (1992)

    Google Scholar 

  53. Holland, J.: Emergence - from chaos to order. Oxford University Press, Oxford (2000)

    Google Scholar 

  54. Hornby, G.S.: Modularity, reuse, and hierarchy: Measuring complexity by measuring structure and organisation. Complexity 13(2), 50–61 (2007)

    Article  MathSciNet  Google Scholar 

  55. Johnson, J.: Hypernetworks for reconstructing the dynamics of multilevel systems. In: Proceedings of European Conference on Complex Systems (November 2006)

    Google Scholar 

  56. Johnson, J.: Multidimensional Events in Multilevel Systems, pp. 311–334. Physica-Verlag HD (2007)

    Google Scholar 

  57. Kefalas, P., Eleftherakis, G., Kehris, E.: Communicating x-machines: A practical approach for formal and modular specification of large systems. Journal of Information and Software Technology 45, 269–280 (2003)

    Article  Google Scholar 

  58. Kefalas, P., Halcombe, M., Eleftherakis, G., Gheorghe, M.: formal method for the development of agent-based systems. In: Plekhanova, V. (ed.) Intelligent Agent Software Engineering. Idea Group Publishing, UK (2003)

    Google Scholar 

  59. Kempe, D., Dobra, A., Gehrke, J.: Gossip-based computation of aggregate information. In: Proceedings of the 44th IEEE Symposium on Foundations of Computer Science (2003)

    Google Scholar 

  60. Kennedy, J., Eberhart, R.C.: Particle swarm optimisation. In: Proceedings of the IEEE International Conference on Evolutionary computation, pp. 1942–1948 (1995)

    Google Scholar 

  61. Kolmogorov, A.N.: On the length of programs for computing finite binary sequences. Prob. Info. Transm. 1, 1–17 (1965)

    Google Scholar 

  62. Koppel, M.: Complexity, depth and sophistication. Complex Systems 1, 1087–1091 (1987)

    MATH  MathSciNet  Google Scholar 

  63. Kubik, A.: Toward a formalization of emergence. Artificial Life 9, 41–66 (2003)

    Article  Google Scholar 

  64. Kung, S.Y.: Digital Neural Networks. PTR Prentice Hall, Englewood Cliffs (1993)

    MATH  Google Scholar 

  65. Lano, K.: The B Language and Method: A Guide to Practical Formal Development. In: FACIT. Springer, Heidelberg (1996)

    Google Scholar 

  66. Lau, C.: Neural networks, theoretical foundations and analysis. IEEE Press, Los Alamitos (1991)

    Google Scholar 

  67. Lovbjerg, M., Rasmussen, T.K., Krink, T.: Hybrid particle swarm optimiser with breeding and subpopulations. In: Proceedings of the third Genetic and Evolutionary Computation Conference (2001)

    Google Scholar 

  68. Mamei, M., Menezes, R., Tolksdorf, R., Zambonelli, F.: Case studies for self-organisation in computer science. Journal of System Architecture 52, 160–443 (2006)

    Google Scholar 

  69. Mamei, M., Zambonelli, F.: Field-based coordination for pervasive multiagent systems. Springer, Heidelberg (2006)

    MATH  Google Scholar 

  70. Messie, D., Oh, J.C.: Environment organisation of roles using polymorphism. In: Weyns, D., Van Dyke Parunak, H., Michel, F. (eds.) E4MAS 2005. LNCS (LNAI), vol. 3830, pp. 251–269. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  71. Milner, R.: A Calculus of Communicating Systems. LNCS, vol. 92. Springer, Heidelberg (1980)

    MATH  Google Scholar 

  72. Milner, R., Parrow, J., Walker, D.: A calculus of mobile processes (i and ii). Inform. and Comput. 100(1), 1–77 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  73. Van Dyke Parunak, H., Brueckner, S.A., Sauter, J.: Digital pheromones for coordination of unmanned vehicles. In: Weyns, D., Van Dyke Parunak, H., Michel, F. (eds.) E4MAS 2004. LNCS (LNAI), vol. 3374. Springer, Heidelberg (2005)

    Google Scholar 

  74. Patel, J., Teacy, W.T.L., Jennings, N.R., Luck, M.: A probabilistic trust model for handling inaccurate reputation sources. In: Herrmann, P., Issarny, V., Shiu, S.C.K. (eds.) iTrust 2005. LNCS, vol. 3477, pp. 193–209. Springer, Heidelberg (2005)

    Google Scholar 

  75. Petri, C.A.: Kommunikation mit Automaten. PhD thesis, Institut fuer Instrumentelle Mathematik, Bonn (1962)

    Google Scholar 

  76. Philippides, A., Smith, T., Husbands, P., O’Shea, M.: Diffusible neuromodulation in real and artificial neural networks. In: AI Symposium, Second International Conference on Cybernetics, Applied Mathematics and Physics: CIMAF 1999. Editorial Academia (1999)

    Google Scholar 

  77. Picard, G., Gleizes, M.P.: Cooperative self-organisation to design robust and adaptive collectives. In: Second International Conference on Informatics in Control, Automation and Robotics (ICINCO 2005), Barcelona, Spain, September 14–17, pp. 236–241. INSTICC Press (2005)

    Google Scholar 

  78. Platon, E., Mamei, M., Sabouret, N., Honiden, S., Parunak, H.V.D.: Mechanisms for environmenrts in multi-agent systems: Survey and applications. Auton. Agent Multi-Agent Syst. 14, 31–47 (2007)

    Article  Google Scholar 

  79. Ramchurn, S., Huynh, D., Jennings, N.R.: Trust in multiagent systems. The Knowledge Engineering Review 19(1), 1–25 (2004)

    Article  Google Scholar 

  80. Ramchurn, S.D., Jennings, N.R., Sierra, C., Godo, L.: Devising a trust model for multi-agent interactions using confidence and reputation. Applied Artificial Intelligence, pp. 833–852 (2004)

    Google Scholar 

  81. Randers, J.: Elements of the System Dynamics Method. MIT Press, Cambridge (1980)

    Google Scholar 

  82. Ratnasamy, S., Karp, B.: Ght: A geographic hash table for data-centric storage. In: Proceedings of the international workshop on wireless sensor networks and applications, Atlanta. ACM Press, New York (2002)

    Google Scholar 

  83. Ronald, E., Sipper, M.: Design, observation, surprise! a test of emergence. Artifcial Life 5, 225–239 (1999)

    Article  Google Scholar 

  84. Rouff, C., Hinchey, M., Rash, J., Truszkowski, W., Gordon-Spears, D.: Formal Methods and Agent-based Systems. Springer, Heidelberg (2006)

    Google Scholar 

  85. Ryan, A.: Emergence is coupled to scope, not level. Nonlinear Sciences (2007)

    Google Scholar 

  86. Sawyer, R.K.: Simulating emergence and downward causation in small groups. In: Proceedings of the Second International Workshop on Multi-Agent Based Simulation, pp. 49–67. Springer, Berlin (2001)

    Chapter  Google Scholar 

  87. Di Marzo Serugendo, G., Gleizes, G., Glize, P.: Self-organisation and emergence in multi-agent systems. The Knowledge Engineering Review 20, 165–189

    Google Scholar 

  88. Shalizi, C.: Causal Architecture, Complexity and Self-Organization in Time Series and Cellular Automata. PhD thesis, University of Michigan (2001)

    Google Scholar 

  89. Shalizi, C.R., Crutchfield, J.P.: Computational mechanics - pattern and prediction, structure and simplicity. Journal of Statictical Physics 104, 819–881 (2001)

    MathSciNet  Google Scholar 

  90. Shalizi, C.R., Shalizi, K.L.: Optimal non-linear prediction of random fields on networks. Discrete Mathematics and Theoretical Computer Science, 11–30 (2003)

    Google Scholar 

  91. Shalizi, C.R., Shalizi, K.L.: Blind construction of optimal nonlinear recursive predictors for discrete sequences. In: Chickering, M., Halpern, J.J. (eds.) Uncertainty in Artificial Intelligence: Proceedings of the Twentieth Conference. AUAI Press (2004)

    Google Scholar 

  92. Silberstein, M., McGeever, J.: The search for ontological emergence. The Philosophical Quarterly 49(195), 201–214 (1999)

    Article  Google Scholar 

  93. Spivey, J.M.: The Z notation: a reference manual. Prentice-Hall, Englewood Cliffs (1989)

    MATH  Google Scholar 

  94. Sudeikat, J., Renz, W.: Toward requirements engineering for self-organising multi-agent systems. In: Proceedings of the First IEEE International Conference on self-adaptive and self-organising systems (SASO 2007), pp. 299–302 (2006)

    Google Scholar 

  95. Sudeikat, J., Renz, W.: Building complex adaptive systems: On engineering self-organising multi-agent systems. In: Application of complex adaptive systems. IDEA (2007)

    Google Scholar 

  96. Sudeikat, J., Renz, W.: Toward systemic mas development: Enforcing decentralised self-organisation by composition and refinement of archetype dynamics. In: Engineering Environment-Mediated Multiagent Systems (EEMAS 2007). LNCS. Springer, Heidelberg (2007)

    Google Scholar 

  97. Tononi, G., Sporns, O., Edelman, G.M.: A measure for brain complexity: Relating functional seggregation and integration in the nervous system. PNAS 91, 5033–5037 (1994)

    Article  Google Scholar 

  98. Turing, A.M.: On computable numbers, with an application to the entscheidungsproblem. Proc. Lond. Math. Soc. 42, 230–265

    Google Scholar 

  99. Varela, F.: Principles of Biological Autonomy. Elsevier, New York (1979)

    Google Scholar 

  100. Vigano, F., Fornara, N., Colombetti, M.: An event driven approach to norms in artificial institutions. In: Boissier, O., Padget, J., Dignum, V., Lindemann, G., Matson, E., Ossowski, S., Sichman, J.S., Vázquez-Salceda, J. (eds.) ANIREM 2005 and OOOP 2005. LNCS (LNAI), vol. 3913, pp. 142–154. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  101. Weyns, D., Holvoet, T.: A formal model for situated multi-agent systems. Fundamenta Informaticae 63(2–3), 125–158 (2004)

    MATH  MathSciNet  Google Scholar 

  102. Weyns, D., Vizzari, G., Holvoet, T.: Environments for situated multi-agent systems: Beyond infrastructure. In: Weyns, D., Van Dyke Parunak, H., Michel, F. (eds.) E4MAS 2005. LNCS (LNAI), vol. 3830. Springer, Heidelberg (2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, University College London,  

    Chih-Chun Chen & Christopher D. Clack

  2. Department of Oncology and Biochemistry, University College London,  

    Sylvia B. Nagl

Authors
  1. Chih-Chun Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sylvia B. Nagl
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Christopher D. Clack
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Old Dominion University, Norfolk, VA, USA

    Andreas Tolk

  2. University of South Australia, Adelaide, Australia

    Lakhmi C. Jain

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Chen, CC., Nagl, S.B., Clack, C.D. (2009). Complexity and Emergence in Engineering Systems. In: Tolk, A., Jain, L.C. (eds) Complex Systems in Knowledge-based Environments: Theory, Models and Applications. Studies in Computational Intelligence, vol 168. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88075-2_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-88075-2_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88074-5

  • Online ISBN: 978-3-540-88075-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation