Skip to main content
Log in

On the dynamics of judgment: does the butterfly effect take place in human working memory?

  • Original Article
  • Published:
Artificial Life and Robotics Aims and scope Submit manuscript

Abstract

Why do people hesitate—to do something, or not to do something—even when the data available to them remain constant? The neural model of human working memory (WM) we present in this paper explains hesitation as an emergent property of a complex dynamic structure of stored/processed information. WM is considered as a geometric space inhabited by a “society” of memes, i.e., complex informational structures. A large population of identical memes can cause a feeling, judgment, or intention in an individual. The memes navigate all over WM and interact with one another in a way resembling genetic cross-over; hence, new memes are born at several places in WM. Since the birth of contradictory memes is possible, populations of memes contributing to contradictory feelings, judgments, and plans grow in WM and fight for domination. A computer simulation of the process showed that WM's state sometimes goes to a two-focal “strange” attractor. Hence, sudden mental shifts, as, say, from love to hate and back from hate to love, may be caused by minute fluctuations in the densities of meme streams entering WM. The complex system theory calls this phenomenon the “butterfly effect”. We argue that this effect takes place in the human mind and also can take place in an advanced robot.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Shimohara K (1999) Evolutionary systems for brain communication. Proceedings of an International Symposium on Low-Power and High-Speed Chips (COOL Chips II), Kyoto, Japan, p 37–50

  2. Nowak A, Vallacher R (1998) Dynamical social psychology Guilford, New York

    Google Scholar 

  3. Vallacher RR, Nowak A (1994) The stream of social judgment. In: Vallachor RR, Nowak A (eds) Dynamical systems in social psychology. Academic Press, San Diego, p 251–277

    Google Scholar 

  4. Minsky M (1987) The society of mind. Simon & Schuster, New York.

    Google Scholar 

  5. de Garis H, Gers F, Korkin M, et al. (1998) Building an artificial brain using an FPGA-based “CAM-brain machine”. Proceedings of the 3rd International Symposium on Artificial Life and Robotics (AROB III'98), Oita, Japan, p 258–262

  6. Baddeley AD (1999) Essentials of human memory. Psychology Press, Hove

    Google Scholar 

  7. Anderson JR (1993) Rules of the mind. Lawrence Erlbaum, Hillsdale

    Google Scholar 

  8. Tulving E (1995) Organization of memory: quo vadis? In: Gazzaniga MS (ed) The cognitive neurosciences. Bradford Books/MIT Press, Cambridge, p 839–847

    Google Scholar 

  9. Buller A (1998) Sztuczny mózg. To jużnie fantazje. Prószynski i Ska, Warsaw

    Google Scholar 

  10. Buller A, de Garis H (1998) Brain-building strategy: some remarks and questions. Proceedings of the Workshop on Intelligent Information Systems (IIS'98), Malbork, p 188–193

  11. Rosch E (1975) Cognitive representations of semantic categories. J Exp Psychol Gen 104: 192–223

    Article  Google Scholar 

  12. Zadeh L (1965) Fuzzy sets. Inf Control 8:338–353

    Article  MATH  MathSciNet  Google Scholar 

  13. Buller A (1995) Operations on multimodal records: to wards a computational cognitive linguistics. Tech Rep TR-95-027, International Computer Science Institute, Berkeley

    Google Scholar 

  14. Buller A (1996) Fizzy-fuzzy inferencing. In: Furuhashi T, Uchikawa Y (eds) Fuzzy logic, neural networks, and evolutionary computation. Springer, Berlin, p 172–187

    Google Scholar 

  15. Buller A (1999) Fuzziness, mega-networks and CoDi technique. 4th Conference on Neural Networks and Their Applications, May 18–22, Zakopane, Poland

  16. Buller A (2000) MemeStorms: a computational model of human working memory ATR Tech Rep TR-H-300, Kyoto.

  17. Plotkin H (1993) Darwin machines and the nature of knowledge. Harvard University Press, Cambridge

    Google Scholar 

  18. Brodie R (1996) Virus of the mind: the new science of the meme. Integral Press, Seattle

    Google Scholar 

  19. Buller A (2000) Self-organization of mind. PhD Dissertation, Department of Psychology, Warsaw University

  20. Calvin WH (1996) The cerebral code: thinking thought in the mosaic of the mind. Bradford Books/MIT Press, Cambridge

    Google Scholar 

  21. Buller A, Shimohara K (2000) Does the “butterfly effect” take place in human working memory? 5th International Symposium on Artificial Life and Robotics (AROB 5th '00), January 26–28, 2000, Oita, Japan, p 204–207

  22. Casti JL (1994) Complexification: explaining a paradoxical world through the science of surprise. Harper Collins, New York

    Google Scholar 

  23. Gers F, de Garis H, Korkin M (1997) CoDi-1-bit: a simplified cellular automata-based neuron model. Evolution Artificielle (AE '97), Nimes, France, p 211–229

  24. Shimohara K, Hemmi H (1999) Evolving artificial brain (in Japanese). Comput Today 4:4–9

    Google Scholar 

  25. de Garis H, Buller A, Korkin M, et al. (1999) ATR's artificial brain (“CAN-brain”) project: a sample of what individual “CoDi-1-bit” model evolved neural net modules can do with digital and analog I/O. 1st NASA/DoD Workshop on Evolvable Hardware, Pasadena, CA, USA, p 102–110

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Andrzej Buller.

About this article

Cite this article

Buller, A., Shimohara, K. On the dynamics of judgment: does the butterfly effect take place in human working memory?. Artif Life Robotics 5, 88–92 (2001). https://doi.org/10.1007/BF02481344

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02481344

Key words

Navigation