Advertisement

Perspectives

  • Octavian Iordache
Part of the Understanding Complex Systems book series (UCS)

Abstract

Selfdisciplinarity is presented as a necessary step in problem solving for evergrowing complexity systems.

Answering to the demand for systems able to combine technologies, sciences, and engineering into condensed expressions, the polytope project is proposed. This project starts from a general architecture shared by the operational structure of self-evolvable devices, the functional organization of organisms as informational and cognitive systems, and the scientific and engineering methods.

Conceptual, selfware, hardware, fabrication and applications perspectives of this project are sketched.

Keywords

Category Theory Data Cube Hasse Diagram Modular Robot Core Array 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aloupis, G., Collette, S., Damian, M., Demaine, E.D., Flatland, R., Langerman, S., O’Rourke, J., Ramaswami, S., Sacristan, V., Wuhrer, S.: Linear reconfguration of cube-style modular robots. Computational Geometry - Theory and Applications 42, 652–663 (2009)MathSciNetzbMATHCrossRefGoogle Scholar
  2. An, B., Rus, D.: Making Shapes from Modules by Magnification. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (2010)Google Scholar
  3. Baez, J.C., Dolan, J.: Categorification. In: Getzler, E., Kapranov, M. (eds.) Higher Category Theory, Contemp. Math., vol. 230, pp. 1–36. American Mathematical Society (1998)Google Scholar
  4. Baez, J., Stay, M.: Physics, Topology, Logic and Computation: A Rosetta Stone. In: Coecke, B. (ed.) New Structure for Physics. Lecture Notes in Physics. Springer (2008)Google Scholar
  5. Bailey, R.A.: Efficient semi-Latin squares. Statistica Sinica 2, 413–437 (1992)MathSciNetzbMATHGoogle Scholar
  6. Bailly, F.: L’anneau des disciplines. Enquête sur quelques concepts théoriques et gnoséologigues. AFSCET, Paris (2010)Google Scholar
  7. Bailly, F., Longo, G., Montévil, M.: A 2-dimensional geometry for biological time. In: Biologiee Selezioni Naturali Conference, Florence, December 4-8, 2009 (2010)Google Scholar
  8. Bainbridge, W.S., Roco, M.C. (eds.): Managing Nano-Bio-Info-Cogno Innovations: Converging Technologies in Society. Springer Science and Business Media, Berlin (2006)Google Scholar
  9. Bergeron, N., Lam, T., Li, H.: Combinatorial Hopf algebras and Towers of Algebras – Dimension. Quantization and Functorality, arXiv:0710.3744v1 (2011)Google Scholar
  10. Berson, A., Smith, S.J.: Data Warehousing, Data Mining, and OLAP. McGraw-Hill (1997)Google Scholar
  11. Bringsjord, S., Taylor, J., Wojtowicz, R., Arkoudas, K., van Heuvlen, B.: Piagetian Roboethics via Category Theory: Moving Beyond Mere Formal Operations to Engineer Robots Whose Decisions are Guaranteed to be Ethically Correct. In: Anderson, M., Anderson, S. (eds.) Machine Ethics. Cambridge University Press, Cambridge (2010)Google Scholar
  12. Buchli, J., Santini, C.: Complexity engineering, harnessing emergent phenomena as opportunities for engineering. Tech. Rep. Santa Fe Institute Complex Systems Summer School, NM, USA (2005)Google Scholar
  13. Chen, Y., Dehne, F., Eavis, T., Rau-Chaplin, A.: Parallel ROLAP data cube construction on shared nothing multiprocessors. Distributed and Parallel Databases 15, 219–236 (2004)CrossRefGoogle Scholar
  14. Cockett, J.R.B.: What is a good process semantics? (2006), http://pages.cpsc.ucalgary.ca/~robin/talks/estonia.pdf
  15. Conklin, J.: Dialogue mapping: Building shared understanding of wicked problems. John Wiley & Sons, Chichester (2006)Google Scholar
  16. Corfield, D.: Categorification as a Heuristic Device. In: Gillies, D., Cellucci, C. (eds.) Mathematical Reasoning and Heuristics. King’s College Publications (2005)Google Scholar
  17. Dau, F. (ed.): Proceedings of the 1st CUBIST Workshop 2011. CEUR-WS, vol. 753 (2011)Google Scholar
  18. de Castro, L.N.: Fundamentals of Natural Computing: Basic Concepts, Algorithms, and Applications. CRC Press (2006)Google Scholar
  19. Dehne, F., Eavis, T., Rau-Chaplin, A.: The cgmCUBE project : Optimizing parallel data cube generation for ROLAP. Distrib. Parralel Databases 19, 29–62 (2006)CrossRefGoogle Scholar
  20. DeLisi, P.S.: The Glass bead Game Linking Interdependence and organizational learning (1999), http://www.org-synergies.com/docs/Glass-Bead-Game.pdf
  21. Engstrom, D., Kelso, J.: Coordination dynamics of the complementary nature. Gestalt Theory 30(2), 121–134 (2008)Google Scholar
  22. Fajstrup, L., Goubault, E., Raussen, M.: Algebraic topology and concurrency. Theoret. Comput. Sci. 357(1-3), 241–278 (2006)MathSciNetzbMATHCrossRefGoogle Scholar
  23. Gilpin, K., Rus, D.: Modular Robot Systems: From Self-Assembly to Self-Disassembly. IEEE Robotics and Automation Magazine 17(3), 38–53 (2010)CrossRefGoogle Scholar
  24. Goldstein, S.C., Campbell, J.D., Mowry, T.C.: Programmable matter. IEEE Comput. 38(6), 99–101 (2005)CrossRefGoogle Scholar
  25. Haikonen, P.O.: Robot Brains: Circuits and Systems for Conscious Machines. Wiley & Sons, Chichester (2007)Google Scholar
  26. Haken, H.: Information and Self-Organization A Macroscopic Approach to Complex Systems. Springer, Berlin (1999)Google Scholar
  27. Han, J., Kamber, M., Pei, J.: Data Mining: Concepts and Techniques, 3rd edn. Morgan Kaufmann (2011)Google Scholar
  28. Hesse, H.: The Glass Bead Game. Holt, Rinehart and Winston, Inc., New York (1969)Google Scholar
  29. Iordache, O.: Evolvable Designs of Experiments Applications for Circuits. J. Wiley VCH, Weinheim (2009)CrossRefGoogle Scholar
  30. Iordache, O.: Polystochastic Models for Complexity. Springer, Heidelberg (2010)zbMATHCrossRefGoogle Scholar
  31. Joswig, M., Ziegler, G.M.: A neighborly cubical 4-polytope. Electronic Geometry Models, No. 2000.05.003, C45 Master.poly. (2000)Google Scholar
  32. Kephart, J.O., Chess, D.M.: The vision of autonomic computing. IEEE Computer 36(1), 41–50 (2003)CrossRefGoogle Scholar
  33. Nagpal, R.: Programmable self-assembly using biologically-inspired multiagent control. In: Proceedings of the 1st International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), pp. 418–425. ACM Press, New York (2002)CrossRefGoogle Scholar
  34. Nicolescu, B.: Manifesto of Transdisciplinarity. SUNY Press, New York (2002)Google Scholar
  35. Nicolescu, B.: Transdisciplinarity-Past, Present and Future. In: Haverkort, B., Reijntjes, C. (eds.) Moving Worldviews - Reshaping Sciences, Policies and Practices for Endogenous Sustainable Development, pp. 142–166. COMPAS Editions, Holland (2006)Google Scholar
  36. Piaget, J.: Classification des sciences et principaux courants épistémologiques contemporains. In: Piaget, J. (ed.) Logique et Connaissance Scientifique, Gallimard, Paris, pp. 1151–1224 (1967)Google Scholar
  37. Piaget, J., Garcia, R.: Psychogenesis and the History of Science. Columbia University Press, New York (1989)Google Scholar
  38. Schweikardt, E., Gross, M.D.: Experiments in design synthesis when behaviour is determined by shape. Pers Ubiquit. Comput. 13, 123–132 (2011)CrossRefGoogle Scholar
  39. Scott, B., Shurville, S.: Epistemological Unification of the Disciplines: The Contributions of Socio-Cybernetics. In: Proceedings of the Sixth European Congress on Systems Science, Paris, France (2005)Google Scholar
  40. Sharp, P.A., Cooney, C.L., Kastner, M.A., Lees, J., Sasisekharan, R., Yaffee, M.A., Bahatia, S.N., Jacks, T.E., Lauffenburger, D.A., Langer, R., Hammond, P.T., Sur, M.: The Third Revolution: The Convergence of the Life Sciences, Physical Sciences, and  Engineering. MIT White Paper (2011)Google Scholar
  41. Sharp, P.A., Langer, R.: Promoting Convergence in Biomedical Science. Science 333, 527 (2011)CrossRefGoogle Scholar
  42. von Stillfried, N.: What about Transdisciplinarity? Its Past, its Present, its Potential... and a Proposal. In: Transdisciplinarity and the Unity of Knowledge: Beyond the Science and Religion Dialog, Philadelphia, Pennsylvania (2007)Google Scholar
  43. Whitesides, G.M., Grzybowski, B.: Self-assembly at all scales. Science 295, 2418–2421 (2002)CrossRefGoogle Scholar
  44. Würtz, R.P. (ed.): Organic Computing: Series: Understanding Complex Systems. Springer (2008)Google Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.PolystochasticMontrealCanada

Personalised recommendations