Article View: comp.robotics
Article #1870neural nets using programmable logic arrays ...
From: Gary Murphy
Date: Tue, 26 Jan 1993 02:46
Date: Tue, 26 Jan 1993 02:46
167 lines
8841 bytes
8841 bytes
I don't know about the hughes chip (sounds interesting) but I do know the adaptive logic networks can be implemented using standard programmable logic arrays; what follows is Bill Armstrong's announcement of the expiration of the ALN patent on these hardware nets: Newsgroups: comp.ai Path: ie.utoronto.ca!drill.me!skule.ecf!torn!spool.mu.edu!yale.edu!yale!gumby!destroyer!cs.ubc.ca!unixg.ubc.ca!kakwa.ucs.ualberta.ca!alberta!arms From: arms@cs.UAlberta.CA (Bill Armstrong) Subject: ALN patent expires Message-ID: <arms.727650547@spedden> Summary: Patent on adaptive logic networks expired on Jan. 20, 1993. Keywords: adaptive logic network Sender: news@cs.UAlberta.CA (News Administrator) Nntp-Posting-Host: spedden.cs.ualberta.ca Organization: University of Alberta, Edmonton, Canada Date: Thu, 21 Jan 1993 21:09:07 GMT Lines: 141 After 17 years, the U.S. patent on adaptive logic networks has run its course, and the material covered by the patent is now in the public domain, free for anyone to use without paying: W. Armstrong, Adaptive Boolean Logic Element, U. S. Patent 3934231, filed Feb. 28, 1974 (filings in various other countries followed), patent granted on Jan. 20, 1976, assigned to Dendronic Decisions Limited, now located at 3624 - 108 Street, Edmonton, Alberta, T6J 1B4, Tel. (403) 438-1103. The patent covered what is essentially the backpropagation algorithm for training logic networks, except that in the ALN context it was called "heuristic responsibility". There were actually three kinds of heuristic responsibility covered, one of which was a steepest descent approach corresponding almost directly to backprop. It was found not to work very well. It would end to get stuck at local minima of error. Two other algorithms were given, called "latest error" and "global search" which worked much better. There are still traces of the "latest error" heuristic in the atree release 2.7 software for Windows 3.x and atree release 2.0 for Unix. The latter programs use the same adaptation algorithm; the advantage of 2.7 is that it has extensive on-line documentation, while the advantage of atree 2.0 is portability. The patent had three constructive reductions to practice in an effort to be *generic*, i.e. to cover *everything* which was a case of heuristic responsibility. The last claim covered a digital logic circuit having elements with "heuristic responsibility" leads. As a consequence of the expiration, one can hope that a large part of ALN technology will end up in the public domain. Of course it is still possible to patent improvements, but these can only be non-obvious ones. As many people have discovered, ALNs learn and execute very quickly. In fact, they are at the very limits of speed for digital logic circuits. This means that they will be around for a long time. Well over 5000 people have obtained the software on Internet or CompuServe, and some interesting applications have been done. Those who are interested in this approach to high speed neural networks can get the the atree adaptive logic network simulation package as follows (N. B. the expiration of the patent has nothing to do with the copyright on the atree software, which has not expired!): The atree adaptive logic network (ALN) simulation package, atree release 2.7, is available via anonymous ftp from menaik.cs.ualberta.ca [129.128.4.241] in pub/atre27.exe (ftp in binary mode). It runs on IBM PCs and compatibles under Windows 3.x. Included is documentation and ON-LINE HELP explaining the basic principles of adaptive logic networks, the atree source code and the examples. All C and C++ source code is provided. Atree release 2.7 is available in either of two files in pub/ on menaik: atre27.exe and a27exe.exe. The file atre27.exe contains the full C and C++ sources for those who want to study or modify them. The code was developed using Borland C++ 3.1 and Application Frameworks. The other, smaller file contains just the executables. The user can study the adaptive algorithm in the On-Line Help under ALN Technical Notes/The Learning Algorithm. To set up your software on the PC under Windows 3.x, it is recommended that you execute atre27.exe in your main directory, whereupon it will create a subdirectory atree_27 and extract everything into it. Running "setup" in the latter directory will create a group of icons you can use to invoke demos and the facilities for programming adaptive logic network applications in the lf language. The "Open" command gives you access to numerous instructive examples. Clicking on the Help button gives you access to explanations of theory and code. The Unix version, atree release 2.0, is in C, and has been ported to Macintosh, Amiga, and other machines. Windows NT will eventually offer another way to use atree on various platforms. There is an electronic mailing list for discussions of ALNs. Mail to alnl-request@cs.ualberta.ca to subscribe or cancel. Your comments on ALN subjects can be emailed to all other subscribers to the list by mailing to alnl@cs.ualberta.ca. A BIBLIOGRAPHY G. v. Bochmann, W. Armstrong, Properties of Boolean Functions with a Tree Decomposition, BIT 13, 1974. pp. 1-13. W. Armstrong, Gilles Godbout: Use of Boolean Tree Functions to Perform High-Speed Pattern Classification and Related Tasks, Dept. d'IRO, Universite de Montreal, Doc. de Travail #53, 1974. (unpublished, except in summary form as follows:) W. Armstrong and G. Godbout, Properties of Binary Trees of Flexible Elements Useful in Pattern Recognition, IEEE 1975 International Conf. on Cybernetics and Society, San Francisco, 1975, IEEE Cat. No. 75 CHO 997-7 SMC, pp. 447-449. W. Armstrong and J. Gecsei, Architecture of a Tree-based Image Processor, 12th Asilomar Conf. on Circuits, Systems and Computers, Pacific Grove, Calif., 1978, pp. 345-349. W. Armstrong and J. Gecsei, Adaptation Algorithms for Binary Tree Networks, IEEE Trans. on Systems, Man and Cybernetics, 9, 1979, pp. 276-285. W. Armstrong, J.-D. Liang, D. Lin, S. Reynolds, Experiments Using Parsimonious Adaptive Logic, Tech. Rept. TR 90-30, Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada, T6G 2H1. This is now available in a revised form via anonymous FTP from menaik.cs.ualberta.ca [129.128.4.241] in pub/atree2.ps.Z (the title of the revised document is Some Results concerning Adaptive Logic Networks). W. Armstrong, A. Dwelly, J.-D. Liang, D. Lin, S. Reynolds, Learning and Generalization in Adaptive Logic Networks, in Artificial Neural Networks, Proceedings of the 1991 International Conference on Artificial Neural Networks ( ICANN'91), Espoo, Finland, June 24-28, 1991, T. Kohonen, K.Makisara, O. Simula, J. Kangas eds. Elsevier Science Publishing Co. Inc. N. Y. 1991, vol. 2, pp. 1173-1176. Allen G. Supynuk, William W. Armstrong, Adaptive Logic Networks and Robot Control, Proc. Vision Interface Conference '92, also called AI/VI/GI '92, Vancouver B. C., May 11-15, 1992, pp. 181 - 186. R. B. Stein, A. Kostov, M. Belanger, W. W. Armstrong and D. B. Popovic, Methods to Control Functional Electrical Stimulation in Walking, First International FES Symposium, Sendai, Japan, July 23 - 25, 1992, pp. 135 - 140. Aleksandar Kostov, Richard B. Stein, William W. Armstrong, Monroe Thomas, Evaluation of Adaptive Logic Networks for Control of Walking in Paralyzed Patients, 14th Ann. Int'l Conf. IEEE Engineering in Medicine and Biology Society, Paris, France, Oct. 29 - Nov. 1, 1992, pp. 1332 - 1334. Ian Parsons, W. W. Armstrong: The Use of Adaptive Logic Nets to Quantify Tar Sands Feed (Draft), available via anonymous ftp from menaik.cs.ualberta.cs [129.128.4.241] in pub/alntarsands.ps.Z. -- *************************************************** Prof. William W. Armstrong, Computing Science Dept. University of Alberta; Edmonton, Alberta, Canada T6G 2H1 arms@cs.ualberta.ca Tel(403)492 2374 FAX 492 1071 -- Gary Lawrence Murphy ---------------- garym@virtual.rose.utoronto.ca University of Toronto, Industrial Eng Dept fax: (416) 971-1373 4 Taddle Creek Rd, Toronto, Ont M5S 1A4 voice: (416) 978-3776 The true destination is always just here, now ----------------------
Technical Details
Message-ID:
<C1Fx1r.IKp@ie.utoronto.ca>Path:
arc1-ca.pugleaf.net!sparky!uunet!cs.utexas.edu!torn!skule.ecf!drill.me!ie.utoronto.ca!garymShow Full Headers
Complete Article Headers
Newsgroups: comp.robotics Path: arc1-ca.pugleaf.net!sparky!uunet!cs.utexas.edu!torn!skule.ecf!drill.me!ie.utoronto.ca!garym From: garym@ie.utoronto.ca (Gary Murphy) Subject: neural nets using programmable logic arrays ... Message-ID: <C1Fx1r.IKp@ie.utoronto.ca> Summary: an alternative to BP networks Keywords: neural_nets adaptive_logic_networks Organization: University of Toronto, Department of Industrial Engineering Date: Tue, 26 Jan 1993 02:46:39 GMT Lines: 167