Skip to main content

The Novamente Artificial Intelligence Engine

  • Chapter
Book cover Artificial General Intelligence

Part of the book series: Cognitive Technologies ((COGTECH))

Summary

The Novamente AI Engine, a novel AI software system, is briefly reviewed. Novamente is an integrative artificial general intelligence design, which integrates aspects of many prior AI projects and paradigms, including symbolic, probabilistic, evolutionary programming and reinforcement learning approaches; but its overall architecture is unique, drawing on system-theoretic ideas regarding complex mental dynamics and associated emergent patterns. The chapter reviews both the conceptual models of mind and intelligence which inspired the system design, and the concrete architecture of Novamente as a software system.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Rakesh Agrawal and Ramakrishnan Srikant. Fast algorithms for mining association rules. In Jorge B. Bocca, Matthias Jarke, and Carlo Zaniolo, editors, Proc. 20th Int. Conf. Very Large Data Bases, VLDB, pages 487–499. Morgan Kaufmann, 1994.

    Google Scholar 

  2. James Albus. Engineering of Mind: An Introduction to the Science of Intelligent Systems. John Wiley and Sons, 2001.

    Google Scholar 

  3. James Albus, N. DeClaris, A. Lacaze, and A. Meystel. Neutral Network Based Planner/Learner for Control Systems. In Proceedings of the 1997 International Conference on Intelligent Systems and Semiotics, pages 75–81, 1997.

    Google Scholar 

  4. Daniel Amit. Modeling Brain Function. Cambridge University Press, 1992.

    Google Scholar 

  5. Bernard Baars. A Cognitive Theory of Consciousness. Cambridge University Press, 1988.

    Google Scholar 

  6. A. D. Baddeley. Working Memory. Oxford University Press, 1998.

    Google Scholar 

  7. Pierre Baldi and G. Wesley Hatfield. DNA Microarrays and Gene Expression: From Experiments to Data Analysis and Modeling. Cambridge University Press, 2002.

    Google Scholar 

  8. A. Barron, J. Rissanen, and B. Yu. The Minimum Description Length Principle in Coding and Modeling. IEEE Transactions on Information Theory, 44 no. 6:2743–2760, 1998.

    Article  MathSciNet  MATH  Google Scholar 

  9. Gregory Bateson. Mind and Nature: A Necessary Unity. Hampton Books, 2002.

    Google Scholar 

  10. Amir Ben-Dor, Ron Shamir, and Zohar Yakini. Clustering Gene Expression Patterns. Journal of Computational Biology, 6:281–297, 1999.

    Article  Google Scholar 

  11. The BlueGene/L Team. An Overview of the BlueGene/L Supercomputer. In Proceedings of the SC-2002 Conference, 2002.

    Google Scholar 

  12. A. Blum and J. Langford. Probabilistic Planning in the GraphPlan Framework. In Proceedings of ECP’99. Springer-Verlag, 1999.

    Google Scholar 

  13. Bila Bollobas. Combinatorics: Set Systems, Hypergraphs, Families of Vectors and Probabilistic Combinatorics. Cambridge University Press, 1986.

    Google Scholar 

  14. Chris Brand. The G-Factor: General Intelligence and its Implications. John Wiley and Sons, 1996.

    Google Scholar 

  15. William Calvin and David Bickerton. Lingua ex Machina: Reconciling Darwin and Chomsky with the Human Brain. MIT Press, 2000.

    Google Scholar 

  16. Gregory Chaitin. Algorithmic Information Theory. Addison-Wesley, 1988.

    Google Scholar 

  17. Haskell Curry and Robert Feys. Combinatory Logic. North-Holland, 1958.

    Google Scholar 

  18. Cycorp. The Syntax of CycL. Technical report, March 2002.

    Google Scholar 

  19. Thomas Dean, Leslie Pack Kaelbling, Jak Kirman, and Ann Nicholson. Planning Under Time Constraints in Stochastic Domains. Artificial Intelligence, 76, 1995.

    Google Scholar 

  20. Daniel Dennett. Brainchildren: Essays on Designing Minds. MIT Press, 1998.

    Google Scholar 

  21. Robert Devaney. An Introduction to Chaotic Dynamical Systems. Westview, 1989.

    Google Scholar 

  22. Julia V. Douthwaite. The Wild Girl, Natural Man, and the Monster: Dangerous Experiments in the Age of Enlightenment. University of Chicago Press, 1997.

    Google Scholar 

  23. Gerald Edelman. Neural Darwinism. Basic Books, 1987.

    Google Scholar 

  24. A. J. Field and P. G. Harrison. Functional Programming. Addison-Wesley, 1988.

    Google Scholar 

  25. Walter Freeman. Neurodynamics. Springer-Verlag, 2000.

    Google Scholar 

  26. Ben Goertzel. The Evolving Mind. Gordon and Breach, 1993.

    Google Scholar 

  27. Ben Goertzel. The Structure of Intelligence. Springer-Verlag, 1993.

    Google Scholar 

  28. Ben Goertzel. Chaotic Logic. Plenum Press, 1994.

    Google Scholar 

  29. Ben Goertzel. From Complexity to Creativity. Plenum Press, 1997.

    Google Scholar 

  30. Ben Goertzel. Creating Internet Intelligence. Plenum Press, 2001.

    Google Scholar 

  31. Ben Goertzel, Cassio Pennachin, and Lucio Coelho. A Systems-Biology Approach for Inferring Genetic Regulatory Networks. In preparation, 2006.

    Google Scholar 

  32. Ben Goertzel, Ken Silverman, Cate Hartley, Stephan Bugaj, and Mike Ross. The Baby Webmind Project. In Proceedings of AISB 00, 2000.

    Google Scholar 

  33. David Goldberg. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, 1989.

    Google Scholar 

  34. Stephen Grossberg. Neural Networks and Natural Intelligence. MIT Press, 1992.

    Google Scholar 

  35. Henrik Grosskreutz. Belief Update in the pGolog Framework. In Proceedings of the International Joint Conference on Artificial Intelligence — IJCAI-01, 2001.

    Google Scholar 

  36. Stuart Hameroff. Ultimate Computing. North Holland, 1987.

    Google Scholar 

  37. Donald Hebb. The Organization of Behavior. John Wiley and Sons, 1948.

    Google Scholar 

  38. Daniel Hillis. The Connection Machine. MIT Press, 1989.

    Google Scholar 

  39. Douglas Hofstadter. Mathematical Themes: Questing for the Essence of Mind and Pattern. Basic Books, 1996.

    Google Scholar 

  40. John Holland. A Mathematical Framework for Studying Learning in Classifier Systems. Physica D, 2, n. 1–3, 1986.

    Google Scholar 

  41. John H. Holland. Adaptation in Natural and Artificial Systems. University of Michigan Press, 1975.

    Google Scholar 

  42. M. Hutter. Towards a universal theory of artificial intelligence based on algorithmic probability and sequential decisions. Proceedings of the 12th European Conference on Machine Learning (ECML-2001), pages 226–238, 2001.

    Google Scholar 

  43. Bipin Indurkhya. Metaphor and Cognition: An Interactionist Approach. Kluwer Academic, 1992.

    Google Scholar 

  44. I. T. Jolliffe. Principal Component Analysis. Springer-Verlag, 1986.

    Google Scholar 

  45. John Josephson and Susan Josephson. Abductive Inference: Computation, Philosophy, Technology. Cambridge University Press, 1994.

    Google Scholar 

  46. Gyorgy Kampis. Self-Modifying Systems in Biology and Cognitive Science. Plenum Press, 1993.

    Google Scholar 

  47. H. Kantz and V. Selman. Pushing the Envelope: Planning, Propositional Logic, and Stochastic Search. In Proceedings of the AAAI Conference 1996, 1996.

    Google Scholar 

  48. Teuvo Kohonen. Self-Organizing Maps. Springer-Verlag, 1997.

    Google Scholar 

  49. John Koza. Genetic Programming. MIT Press, 1992.

    Google Scholar 

  50. Ray Kurzweil. The Age of Spiritual Machines. Penguin Press, 2000.

    Google Scholar 

  51. D. B. Lenat. Cyc: A Large-Scale Investment in Knowledge Infrastructure. Communications of the ACM, 38, no. 11, November 1995.

    Google Scholar 

  52. Stanley Letovsky. Bioinformatics: Databases and Systems. Kluwer Academic, 1999.

    Google Scholar 

  53. Christophet Manning and Heinrich Schutze. Foundations of Statistical Natural Language Processing. MIT Press, 1999.

    Google Scholar 

  54. Jane Mercer. Labeling the Mentally Retarded. University of California Press, 1973.

    Google Scholar 

  55. Judea Pearl. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan-Kaufmann, 1988.

    Google Scholar 

  56. Martin Pelikan. Bayesian Optimization Algorithm: From Single Level to Hierarchy. PhD thesis, University of Illinois at Urbana-Champaign, October 2002.

    Google Scholar 

  57. Roger Penrose. Shadows of the Mind. Oxford University Press, 1997.

    Google Scholar 

  58. Juergen Schmidhuber. Bias-Optimal Incremental Problem Solving. In Advances in Neural Information Processing Systems-NIPS 15. MIT Press, 2002.

    Google Scholar 

  59. John R. Searle. Minds, Brains, and Programs. Behavioral and Brain Sciences, 3:417–457, 1980.

    Article  Google Scholar 

  60. Stuart Shapiro. An Introduction to SNePS 3, pages 510–524. Springer-Verlag, 2000.

    Google Scholar 

  61. Stuart Shieber. Introduction to Unification-Based Approaches to Grammar. University of Chicago Press, 1986.

    Google Scholar 

  62. P. Simard, M. B. Ottaway, and D. H. Ballard. Analysis of Recurrent Backpropagation. In D. Touretzky, G. Hinton, and T. Sejnowsky, editors, Proceedings of the 1988 Connectionist Models Summer School, pages 103–112. Morgan Kaufmann, 1988.

    Google Scholar 

  63. M. Stickel, R. Waldinger, M. Lowry, T. Pressburger, and I. Underwood. Deductive Composition of Astronomical Software from Subroutine Libraries. In Proceedings of the Twelfth Internation Conference on Automated Deduction (CADE-12), pages 341–355, June 1994.

    Google Scholar 

  64. David Stork. Scientist on the Set: An Interview with Marvin Minsky, chapter 2. MIT Press, 2002.

    Google Scholar 

  65. V. Subrahmanian. Nonmonotonic Logic Programming. IEEE Transactions on Knowledge and Data Engineering, 11–1:143–152, 1999.

    Article  Google Scholar 

  66. Richard Sutton and Andrew Barton. Reinforcement Learning. MIT Press, 1998.

    Google Scholar 

  67. Alan Turing. Computing Machinery and Intelligence. McGraw-Hill, 1950.

    Google Scholar 

  68. Francisco Varela. Principles of Biological Autonomy. North-Holland, 1978.

    Google Scholar 

  69. Pei Wang. On the Working Definition of Intelligence. Technical Report CRCC Technical Report 95, Center for Research in Concepts and Cognition, Indiana University at Bloomington, 1995.

    Google Scholar 

  70. Gerhard Weiss, editor. Multiagent Systems. MIT Press, 2000.

    Google Scholar 

  71. Ian Witten and Eibe Frank. Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann, 1999.

    Google Scholar 

  72. Huang Xuedong, Alex Acero, Hsiao-Wuen Hon, and Raj Reddy. Spoken Language Processing: A Guide to Theory, Algorithm and System Development. Prentice Hall, 2001.

    Google Scholar 

  73. A. Zadeh and Janusz Kacprzyk, editors. Fuzzy Logic for the Management of Uncertainty. John Wiley and Sons, 1992.

    Google Scholar 

  74. Mikhail Zak. From Instability to Intelligence: Complexity and Predictability in Nonlinear Dynamics. Springer-Verlag, 1997.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Goertzel, B., Pennachin, C. (2007). The Novamente Artificial Intelligence Engine. In: Goertzel, B., Pennachin, C. (eds) Artificial General Intelligence. Cognitive Technologies. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68677-4_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-68677-4_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23733-4

  • Online ISBN: 978-3-540-68677-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics