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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Burles, Nathan John (2010)
Languages: English
Types: Doctoral thesis
Subjects:
Correlation matrix memories have been successfully applied to many domains. This work implements a production system put forward in [Austin, 2003], to demonstrate its viability as an efficient rule-chaining process. Background information on rule-chaining and CMMs is given, followed by a review of the proposed production system. Throughout the iterative development process, experimentation is performed in order to investigate the effects of changing the properties of vectors used in this system. The results show that generating vectors using the algorithm proposed in [Baum, 1988] with a weight close to log2 of the vector length provides the highest storage capacity. The simple system implemented in this work performs rule-chaining effectively. This leads to the conclusion that the proposed production system is viable, and that this area warrants further work.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [1] Jim Austin, "A production system architecture using a Neural Associative Memory," University of York, York, Unpublished 2003.
    • [2] Jim Austin, "A Review of RAM based Neural Networks," in Fourth International Conference on Microelectronics, Turin, 1994, pp. 58-66.
    • [3] Jim Austin, "Distributed Associative Memories for High Speed Symbolic Reasoning," Fuzzy Sets and Systems, vol. 82, no. 2, pp. 223-233, September 1996.
    • [4] Jim Austin, "Parallel Distributed Computation," in International Conference on Artificial Neural Networks, Brighton, 1992.
    • [5] Jim Austin, "Uncertain Reasoning with RAM based Neural Networks," Journal of Intelligent Systems, vol. 2, no. 4, pp. 121-154, November 1990.
    • [6] Jim Austin and Richard Filer, "Using Neural Networks for Inferencing in Expert Systems," in Neural Networks and Their Applications, John G Taylor, Ed. New York, United States of America: John Wiley & Sons, 1996, ch. 16, pp. 243-.
    • [7] Jim Austin and Thomas J Stonham, "The ADAM Associative Memory," University of York, York, Yellow Report YCS 94, 1986.
    • [8] Eric B Baum, J Moody, and F Wilczek, "Internal representations for associative memory," Biological Cybernetics, vol. 59, no. 4-5, pp. 217-228, September 1988.
    • [9] Rafal Bogacz and Christophe Giraud-Carrier, "A Novel Modular Neural Architecture for RuleBased and Similarity-Based Reasoning," in Hybrid Neural Systems, Stefan Wermter and Ron Sun, Eds. Heidelberg, Germany: Springer-Verlag, 2000, pp. 63-77.
    • [10] Samuel Braunstein. (2009, October) Quantum Information Processing Course website. [Online]. http://www-course.cs.york.ac.uk/qip
    • [11] Jason Brownlee, "Finite State Machines," AI Depot - AI Article Writing Contest, June 2002.
    • [12] David Casasent and Brian Telfer, "High capacity pattern recognition associative processors," Neural Networks, vol. 5, no. 4, pp. 687-698, July-August 1992.
    • [13] Alison Cawsey. (1994, August) School of Mathematics and Computer Science, Heriot Watt University. [Online]. http://www.macs.hw.ac.uk/~alison/ai3notes/section2_4_4.html
    • [14] Rob Davis and Aaron Turner. (2007) AURA library documentation.
    • [15] David Deutsch, "Quantum Theory, the Church-Turing Principle and the Universal Quantum Computer," Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences, vol. 400, no. 1818, pp. 97-117, 1985.
    • [16] Michael Freeman, Michael Weeks, and Jim Austin, "AICP: Aura Intelligent Co-Processor for Binary Neural Networks," in IP Based SOC Design Forum and Exhibition, Grenoble, 2004.
    • [17] Alan Frisch. (2010, January) Logic Programming and Artificial Intelligence Course website. [Online]. http://www-course.cs.york.ac.uk/lpa
    • [18] Paul Gillard. (2007) Department of Computer Science, Memorial University. [Online]. http://web.cs.mun.ca/~paul/cs3724/material/web/notes/node25.html
    • [20] Donald O Hebb, The Organization of Behavior. New York, United States of America: John Wiley and Sons, Inc., 1949, p. 62.
    • [21] Stephen Hobson and Jim Austin, "Improved Storage Capacity in Correlation Matrix Memories Storing Fixed Weight Codes," in 19th International Conference on Artificial Neural Networks: Part I, Limassol, 2009, pp. 728-736.
    • [22] Victoria J Hodge and Jim Austin, "A Comparison of Standard Spell Checking Algorithms and a Novel Binary Neural Approach," IEEE Transactions on Knowledge and Data Engineering, vol. 15, no. 5, pp. 1073-1081, September-October 2003.
    • [23] Damian Isla, "Handling Complexity in the Halo 2 AI," in Game Developers Conference, San Francisco, March 2005.
    • [24] Yaochu Jin. (2010, March) Soft Computing. [Online]. http://www.soft-computing.de
    • [25] Phillip Kaye, Raymond Laflamme, and Michele Mosca, An Introduction to Quantum Computing. Oxford, United Kingdom: OUP Oxford, 2007.
    • [26] Stefan Klinger and Jim Austin, "Chemical Similarity Searching Using a Neural Graph Matcher," in European Symposium on Artificial Neural Networks, Bruges, 2005.
    • [27] Donald Knuth, The Art of Computer Programming, Volume 4, Fascicle 2. Reading, United States of America: Addison-Wesley Professional, 2005.
    • [28] Teuvo Kohonen, Erkki Oja, and Pekka Lehtiö, "Storage and Processing of Information in Distributed Associative Memory Systems," in Parallel Models of Associative Memory, Updated Edition, Geoffrey E Hinton and James A Anderson, Eds. Hillsdale, United States of America: Lawrence Erlbaum Associates, Inc., 1989, ch. 4, pp. 129-170.
    • [29] Daniel Kustrin and Jim Austin, "Connectionist Propositional Logic: A Simple Correlation Matrix Memory Based Reasoning System," in Emergent neural computational architectures based on neuroscience: towards neuroscience-inspired computing, Stefan Wermter, Jim Austin, and David Willshaw, Eds. New York, United States of America: Springer-Verlag, 2001, pp. 534-546.
    • [30] Peter Linz, An Introduction to Formal Languages and Automata, 4th ed. Sudbury, United States of America: Jones and Bartlett Publishers, 2006.
    • [31] John C Martin, Introduction to Languages and the Theory of Computation, 3rd ed. Boston, United States of America: McGraw-Hill, 2003.
    • [32] Edward F Moore, "Gedanken Experiments on Sequential Machines," in Automata Studies, J. McCarthy C. E. Shannon, Ed., 1956, pp. 129-153.
    • [33] Bernard M Moret, The Theory of Computation. Reading, United States of America: AddisonWesley, 1998.
    • [34] Michael A Nielsen and Isaac L Chuang, Quantum Computation and Quantum Information. Cambridge, United Kingdom: Cambridge University Press, 2000.
    • [35] Christos Orovas and Jim Austin, "Cellular Associative Symbolic Processing for Pattern Recognition," in MFCS '98 workshop on Grammar Learning, Opava, 1998, pp. 269-280.
    • [36] Brian D Ripley, Pattern Recognition and Neural Networks. Cambridge, United Kingdom: Cambridge University Press, 1996.
    • [37] Raul Rojas, Neural Networks - A Systematic Introduction. New York, United States of America: Springer, 1996.
    • [38] Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, 2nd ed. Upper Saddle River, United States of America: Prentice Hall, 2003.
    • [39] Robert Schalkoff, Pattern Recognition: Statistical, Structural and Neural Approaches. New York, United States of America: John Wiley & Sons, Inc., 1992.
    • [40] Murray Shanahan and Richard Southwick, Search, Inference and Dependencies in Artificial Intelligence. Chichester, United Kingdom: Ellis Horwood Limited, 1989.
    • [41] Peter Shor, "Algorithms for quantum computation: Discrete logarithms and factoring," in Foundations of Computer Science, Santa Fe, 1994, pp. 124-134.
    • [42] Patrick K. Simpson, Artificial Neural Systems: Foundations, Paradigms, Applications, and Implementations. New York, United States of America: Pergamon Press, Inc., 1990.
    • [43] F S Smailbegovic, G N Gaydadjiev, and S Vassiliadis, "Sparse Matrix Storage Format," in 16th Annual Workshop on Circuits, Systems and Signal Processing, ProRisc, Veldhoven, 2005, pp. 445- 448.
    • [44] Michael Turner and Jim Austin, "Matching performance of binary correlation matrix memories," Transactions of the Society for Computer Simulation International, vol. 14, no. 4, pp. 1637-1648, December 1997.
    • [45] David J Willshaw, Parallel models of associative memories, G E Hinton and J A Anderson, Eds. Hillsdale, United States of America: Erlbaum, 1981.
    • [46] David J Willshaw, O P Buneman, and H C Longuet-Higgins, "Non-Holographic Associative Memory," Nature, vol. 222, no. 5197, pp. 960-962, June 1969.
    • [47] Richard Wilson, "Neural Networks," in Unpublished, available from http://wwwcourse.cs.york.ac.uk/pat/book. United Kingdom, 2010, ch. 7.
    • [48] Richard Wilson. (2009, November) Pattern Recognition and Neural Networks Course website. [Online]. http://www-course.cs.york.ac.uk/pat
    • [49] Lotfi A Zadeh, "Fuzzy Logic, Neural Networks, and Soft Computing," Communications of the ACM, vol. 37, no. 3, pp. 77-84, March 1994.
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