Composability in Cognitive Hierarchies

  • David Rajaratnam
  • Bernhard Hengst
  • Maurice Pagnucco
  • Claude Sammut
  • Michael Thielscher
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9992)

Abstract

This paper develops a theory of node composition in a formal framework for cognitive hierarchies. It builds on an existing model for the integration of symbolic and sub-symbolic representations in a robot architecture consisting of nodes in a hierarchy. A notion of behaviour equivalence between cognitive hierarchies is introduced and node composition operators that preserve this equivalence are defined. This work is significant in two respects. Firstly, it opens the way for a formal comparison between cognitive robotic systems. Secondly, composition, more precisely decomposition, has been shown to be important to many fields, and may therefore prove of practical benefit in the context of cognitive systems.

References

  1. 1.
    Albus, J.S.: Engineering of Mind: An Introduction to the Science of Intelligent Systems. Wiley, New York (2001)Google Scholar
  2. 2.
    Amir, E., Engelhardt, B.: Factored planning. In: Proceedings of IJCAI, pp. 929–935. Morgan Kaufmann (2003)Google Scholar
  3. 3.
    Anderson, J.R.: Rules of the Mind. Lawrence Erlbaum Associates Inc., New Jersey (1993)Google Scholar
  4. 4.
    Belle, V., Levesque, H.J.: Robot location estimation in the situation calculus. J. Appl. Logic 13(4), 397–413 (2015)MathSciNetCrossRefMATHGoogle Scholar
  5. 5.
    Brafman, R.I., Domshlak, C.: Factored planning: how, when, and when not. In: Proceedings of AAAI, pp. 809–814 (2006)Google Scholar
  6. 6.
    Brooks, R.A.: A robust layered control system for a mobile robot. IEEE J. Robot. Autom. 2(1), 14–23 (1986)CrossRefGoogle Scholar
  7. 7.
    Brooks, R.A.: Elephants don’t play chess. Robot. Auton. Syst. 6, 3–15 (1990)CrossRefGoogle Scholar
  8. 8.
    Cerexhe, T.J., Rajaratnam, D., Saffidine, A., Thielscher, M.: A systematic solution to the (de-)composition problem in general game playing. In: Proceedings of ECAI, pp. 195–200 (2014)Google Scholar
  9. 9.
    Clark, K., Hengst, B., Pagnucco, M., Rajaratnam, D., Robinson, P., Sammut, C., Thielscher, M.: A framework for integrating symbolic and sub-symbolic representations. In: Proceedings of IJCAI, pp. 2486–2492 (2016)Google Scholar
  10. 10.
    De Giacomo, G., Sardiña, S.: Automatic synthesis of new behaviors from a library of available behaviors. In: Proceedings of IJCAI, pp. 1866–1871 (2007)Google Scholar
  11. 11.
    Hengst, B.: Hierarchical approaches. In: Wiering, M., van Otterlo, M. (eds.) Reinforcement Learning: State of the Art. Adaptation, Learning, and Optimization, vol. 12, pp. 293–323. Springer, Heidelberg (2011). doi:10.1007/978-3-642-27645-3_9 CrossRefGoogle Scholar
  12. 12.
    Jaeger, H., Christaller, T.: Dual dynamics: designing behavior systems for autonomous robots. Artif. Life Robot. 2(3), 108–112 (1998)CrossRefGoogle Scholar
  13. 13.
    Laird, J.E., Kinkade, K.R., Mohan, S., Xu, J.Z.: Cognitive robotics using the soar cognitive architecture. Cognitive Robotics AAAI Technical report WS-12-06, pp. 46–54 (2012)Google Scholar
  14. 14.
    Laird, J.E., Newell, A., Rosenbloom, P.S.: SOAR: an architecture for general intelligence. Artif. Intell. 33(1), 1–64 (1987)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Lee, D., Kim, H., Myung, H.: GPU-based real-time RGB-D 3D SLAM. In: Proceedings Ubiquitous Robots and Ambient Intelligence (URAI), pp. 46–48. IEEE (2012)Google Scholar
  16. 16.
    Nilsson, N.: Teleo-reactive programs and the triple-tower architecture. Electron. Trans. Artif. Intell. 5, 99–110 (2001)Google Scholar
  17. 17.
    Sacerdoti, E.D.: Planning in a hierarchy of abstraction spaces. Artif. Intell. 5(2), 115–135 (1974)CrossRefMATHGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • David Rajaratnam
    • 1
  • Bernhard Hengst
    • 1
  • Maurice Pagnucco
    • 1
  • Claude Sammut
    • 1
  • Michael Thielscher
    • 1
  1. 1.University of New South WalesSydneyAustralia

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