[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content

Dynamic Models for Intention (Goal-Directedness) Are Required by Truly Intelligent Robots

  • Conference paper
Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3496))

Included in the following conference series:

  • 1443 Accesses

Abstract

Intelligent behavior is characterized by flexible and creative pursuit of endogenously defined goals. Intentionality is a key concept by which to link brain dynamics to goal-directed behavior, and to design mechanisms for intentional adaptations by machines. Evidence from vertebrate brain evolution and clinical neurology points to the limbic system as the key forebrain structure that creates the neural activity which formulate goals as images of desired future states. The behavior patterns created by the mesoscopic dynamics of the forebrain take the form of hypothesis testing. Predicted information is sought by use of sense organs. Synaptic connectivity of the brain changes by learning from the consequences of actions taken. Software and hardware systems using coupled nonlinear differential equations with chaotic attractor landscapes simulate these functions in free-roving machines learning to operate in unstructured environments.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Freeman, W.J.: Societies of Brains. A Study in the Neuroscience of Love and Hate. Lawrence Erlbaum Associates, Hillsdale (1995)

    Google Scholar 

  2. Herrick, C.J.: The Brain of the Tiger Salamander. Univ. Chicago Press, IL (1948)

    Google Scholar 

  3. Barrie, J.M., Freeman, W.J., Lenhart, M.D.: Spatiotemporal Analysis of Prepyriform, Visual, Auditory and Somesthetic Surface EEG in Trained Rabbits. J. Neurophysiol 76, 520–539 (1996)

    Google Scholar 

  4. Singer, W., Gray, C.M.: Visual Feature Integration and the Temporal Correlation Hypothesis. Annual Review of Neuroscience 18, 555–586 (1995)

    Article  Google Scholar 

  5. Haken, H.: Synergetics: An Introduction. Springer, Berlin (1983)

    MATH  Google Scholar 

  6. Freeman, W.J.: A Neurobiological Theory of Meaning in Perception. Part 1. Information and Meaning in Nonconvergent and Nonlocal Brain Dynamics. Int. J. Bif. Chaos 13, 2493–2511 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  7. Freeman, W.J.: Origin, Structure and Role Of Background EEG activity. Part 3. Neural frame classification. Clin. Neurophysiol (2005)

    Google Scholar 

  8. Freeman, W.J.: Mass Action in the Nervous System. Academic Press, New York (2005), Available in electronic form on http://sulcus.berkeley.edu

    Google Scholar 

  9. Freeman, W.J., Chang, H.-J., Burke, B.C., Rose, P.A., Badler, J.: Taming Chaos: Stabilization of Aperiodic Attractors by Noise. IEEE Trans. Circuits Systems 44, 989–996 (1997)

    Article  MathSciNet  Google Scholar 

  10. Kozma, R., Freeman, W.J.: Chaotic Resonance: Methods and Applications For Robust Classification Of Noisy and Variable Patterns. Int. J. Bif. Chaos 10, 2307–2322 (2001)

    Google Scholar 

  11. Kozma, R., Freeman, W.J., Erdí, P.: The KIV Model - Nonlinear Spatiotemporal Dynamics of the Primordial Vertebrate Forebrain. Neurocomputing 52, 819–826 (2003)

    Article  Google Scholar 

  12. Freeman, W.J.: Neurodynamics. An Exploration of Mesoscopic Brain Dynamics. Springer, London (2000)

    MATH  Google Scholar 

  13. Skarda, C.A., Freeman, W.J.: How Brains Make Chaos in Order to Make Sense of the World. Behavioral and Brain Sciences 10, 161–195 (1987)

    Article  Google Scholar 

  14. Tsuda, I.: Toward An Interpretation of Dynamical Neural Activity in Terms of Chaotic Dynamical Systems. Behav. Brain Sci. 24, 793–847 (2001)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Freeman, W.J. (2005). Dynamic Models for Intention (Goal-Directedness) Are Required by Truly Intelligent Robots. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_3

Download citation

  • DOI: https://doi.org/10.1007/11427391_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25912-1

  • Online ISBN: 978-3-540-32065-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics