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 SCS-C(1)                EDUCATIONAL TOOLS                SCS-C(1)



 NAME
      scsc - a simple classifier system in C


 SYNOPSIS
      scsc [ options ]

           [-N, --no-noise-in-auction]

           [-S, --no-specificity-in-auction]

           [-b, --batch]

           [-h, --help]

           [-V, --version]

           [-W, --warranty]

           [-c, --classifier-data <classifier data file name>]

           [-d, --detector-data <detector data file name>]

           [-e, --environmental-
           data <environmental data file name>]

           [-g, --genetics-data <GA data file name>]

           [-r, --reinforcement-
           data <reinforcement data file name>]

           [-t, --timekeeper-data <timekeeper data file name>]

           [-l, --log-file <log file name>]

           [-p, --plot-file <plot file name>]

           [-s, --seed-for-random <seed value>]

           [-T, --time-steps <number>]


 DESCRIPTION
      scsc implements the simple  classifier  system  SCS-C;  a  C
      translation  of Goldberg's Pascal SCS (refer to the SEE ALSO
      section below).

      scsc's input and output streams, and some  of  it's  default
      parameters  may  be  changed  using various options (see the
      OPTIONS section below).





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 OPTIONS
      -N, --no-noise-in-aution
           Turn off  the  noise  generating  function  during  the
           apportionment of credit.

      -S, --no-specificity-in-auction
           Turn off default hierarchy seeking (you can also assign
           zero  values  to  classifier-data  parameters  bid2 and
           ebid2.)

      -T, --time-steps number
           Run the system for  number  of  timesteps.   (Note:  on
           non-UNIX  machines  the user may interrupt scsc by hit-
           ting a key on the keyboard. He is then prompted  if  he
           want's  to  abort  execution,  or go on: Halt (y/n)? On
           UNIX systems this  facility  is  currently  not  imple-
           mented, we use the shell's job control mechanism.)

      -b, --batch
           Run scsc in batch mode, ie. don't prompt the  user  for
           any  input;  eg.  the random number generator's seed is
           initialized with a default value  (0.02021965),  unless
           specified  otherwise  with  the `-s, --seed-for-random'
           flag.

      -c, --classifier-data filename
           The classifier data  will  be  read  in  from  filename
           (defaults to scs.cls).

      -d, --detector-data filename
           The  detector  data  will  be  read  in  from  filename
           (defaults  to  scs.det).  (Unused in the contributed 6-
           bit multiplexer example.)

      -e, --environmental-data filename
           The environmental data will be read  in  from  filename
           (defaults to scs.env).

      -g, --genetics-data filename
           The genetic algorithm parameters will be read  in  from
           filename (defaults to scs.gen).

      -h, --help
           Print a usage message containing all options.

      -l, --log-file filename
           Logging information will go to  filename  (defaults  to
           scs.log).

      -p, --plot-file filename
           Plot data will go to filename (defaults to scs.plt).




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 SCS-C(1)                EDUCATIONAL TOOLS                SCS-C(1)



      -r, --reinforcement-data filename
           The reinforcement  parameters  will  be  read  in  from
           filename (defaults to scs.rfc).

      -s, --seed-for-random seed value
           Set the random number generator's seed  with  the  real
           seed value.

      -t, --timekeeper-data filename
           The time keeper's  parameters  will  be  read  in  from
           filename (defaults to scs.tim).

      -V, --version
           Print a version and copyright message; you will also be
           informed  which  random  number  generator is currently
           compiled into scsc.

      -W, --warranty
           Print a warranty information message.


 SEE ALSO
      David E. Goldberg, Genetic Algorithms in  Search,  Optimiza-
      tion,  and  Machine  Learning,  Addison-Wesley,  Reading MA,
      1989.

      csh(1), jazz(1)


 AUTHOR
      Copyright (C) 1993, 1994 by Joerg Heitkoetter
      Systems Analysis Group, University of Dortmund, Germany.
      Research and Development Group, EUnet Deutschland GmbH.
      Send bugs, comments, etc., to <joke@Germany.EU.net>


 AVAILABILITY
      This work is protected by the terms of the GNU General  Pub-
      lic  License.  Please refer to the LICENSE file accompanying
      the sources of this software package for a lengthy,  boring,
      but absolute complete description.

      SCS-C is available via ENCORE  in  it's  classifier  systems
      section as file ../EC/CFS/src/scsc-1.3j.tar.gz


 THANKS
      To all of those who  showed  their  interest  and/or  helped
      debugging  the  program  and  sent  fixes,  in  the order of
      appearance in my mailbox:





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 SCS-C(1)                EDUCATIONAL TOOLS                SCS-C(1)



      Uwe Schnepf<Uwe.Schnepf@gmd.de>
      Looser Bjoern<ia90loos@htl-bw.ch>
      Marc Levitt<Marc.Levitt@Eng.Sun.COM>
      Amin Hammad<c42394a@nucc.cc.nagoya-u.ac.jp>
      Bill Gillock<whg@houston.geoquest.slb.com>
      Wajid Khan<wajid@ee.umr.edu>
      Friedrich Krebs<fritz@theory.informatik.uni-kassel.de>
      Ms. Wan Hua<a92351@cs.ait.ac.th>
      Sergio<sergio@cic.unb.br>
      Jacques Bonneville<bonnev@lisisun.univ-lyon1.fr>
      Loia Vincenzo<loia@udsab.dia.unisa.it>
      Joey Baumgartner<jbaumgar@ringer.cs.utsa.edu>
      Pankaj Kanwar<pankaj@magenta.me.fau.edu>
      Joseph Taylor Potts<potts@cse.uta.edu>
      Martyn Amos<martyn@dcs.warwick.ac.uk>
      John Prior<jprior@soleil.esa.lanl.gov>
      Frank Hoffmann<hoefi@hp1.ang-physik.uni-kiel.d400.de>
      Marc M. Lankhorst<lankhors@cs.rug.nl>
      Martin Schuetz<schuetz@edna.informatik.uni-dortmund.de>
      D. Poulet<csc270@cent1.lancs.ac.uk>
      Kwok-Ching Tsui<ktsui@dcs.kcl.ac.uk>
      Jorge Gabriel Ponce de Leon Sanchez<al702782@academ01.mty.itesm.mx>
      Andreas Frick<afr@aifb.uni-karlsruhe.de>
































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