Modelling dynamics of cognitive agents by higher-order potentialities

ABSTRACT

In the development of disciplines addressing dynamics, such as Mathematics and Physics, a major role was played by the assumption that processes can be modelled by introducing certain state properties (also called potentialities) that anticipate in which respect a next state will be different. The current paper is a first exploration of this perspective to analyse and model dynamics. Potentiality-based modelling subsumes quantitative, numerical modelling approaches, such as Dynamical Systems Theory (DST), and qualitative or symbolic modelling approaches to dynamics, such as BDI-modelling, and is applicable to model dynamics in a wide variety of (cognitive and noncognitive) disciplines. Thus, the modelling of dynamics of cognitive agents can be fully integrated with the modelling of other phenomena in Nature.

REFERENCES

• 1: Aristotle (350 BC). Physica (translated by R. P. Hardie and R. K. Gaye).
• 2: Aristotle (350 BC). De Motu Animalium On the Motion of Animals (translated by A. S. L. Farquharson).
• 3: Ashby, R. (1952). Design for a Brain. Chapman & Hall, London. Revised second edition, 1960.
• 4: Descartes, R. (1633). The World or Treatise on Light. Withdrawn from publication, 1633. Also in: Descartes, R. (1998), Descartes: The World and Other Writings (edited by Stephen Gaukroger). Cambrige University Press. (translated by M. S. Mahoney).
• 5: Patrick Gebhard, ALMA: a layered model of affect, Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems, July 25-29, 2005, The Netherlands [doi>10.1145/1082473.1082478]
• 6: Timothy van Gelder , Robert F. Port, It's about time: an overview of the dynamical approach to cognition, Mind as motion: explorations in the dynamics of cognition, Massachusetts Institute of Technology, Cambridge, MA, 1996
• 7: Leibniz, G. W. von (1956). Philosophical Papers and Letters, LeRoy E. Loemker, ed., Chicago: University of Chicago Press, 1956.
• 8: Newton, I. (1729). The Mathematical Principles of Natural Philosophy; Newton's Principles of Natural Philosophy, Dawsons of Pall Mall, 1968.
• 9: Robert F. Port , Timothy van Gelder, Mind as motion: explorations in the dynamics of cognition, Massachusetts Institute of Technology, Cambridge, MA, 1996
• 10: Rao, A. S., Georgeff, M. P. (1991). Modeling rational agents within a BDI architecture. In: R. Fikes and E. Sandewall (eds.), Proc. of the Second Conference on Knowledge Representation and Reasoning, Morgan Kaufman, pp. 473--484.
• 11: Scheutz, M., and Sloman, A. (2001). Affect and Agent Control: Experiments with Simple Affective States. In: Proceedings of IAT 2001, World Scientific Publishers.
• 12: Taylor, B. (1715). Methodus Incrementorum Directa et Inversa.

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence
            Subjects: Intelligent agents

Additional Classification:
  I. Computing Methodologies
  I.6 SIMULATION AND MODELING
      I.6.5 Model Development
          Subjects: Modeling methodologies

General Terms:
Design