PDP++ version 2.0

[Randall C. O'Reilly]

	     ANNOUNCING: The PDP++ Software, version 2.0

Authors: Randall C. O'Reilly, Chadley K. Dawson, and James L. McClelland

The PDP++ software is a neural-network simulation system written
in C++.  It represents the next generation of the PDP software
released with the McClelland and Rumelhart "Explorations in Parallel
Distributed Processing Handbook", MIT Press, 1987.  It is easy enough
for novice users, but very powerful and flexible for research use.

The current version is 2.0, released August, 2000, which is a major
upgrade from previous versions, as detailed below.

The software can be obtained by anonymous ftp from:
Anonymous FTP Site: 	ftp://grey.colorado.edu/pub/oreilly/pdp++ *or*
			ftp://cnbc.cmu.edu/pub/pdp++/		  *or*
			unix.hensa.ac.uk/mirrors/pdp++/

For more information, see our web page:
  WWW Page:   http://www.cnbc.cmu.edu/PDP++/PDP++.html

There is a 250 page (printed) manual and an HTML version available 
on-line at the above address.

The new features in 2.0 include:
---------------------------------
  o MS Windows platform fully supported (using CYGWIN environment)
  o Project View window for GUI onto project/processes & specs
  o Enviro View rewritten, GUI for event/pattern layout, etc.
  o Grid View rewritten, interactively configurable grid layout
  o Easy viewing of entire network weights in grid log
  o Easy cluster plot interface, displayed in graph log
  o GUI for interactive construction improved
  o Context-senstive help via "Help" menu on all objects (via HTML)
  o Lots and lots of bug fixes, minor improvements: every known way
    to crash software has been fixed!

Software Features:
==================

  o Full Graphical User Interface (GUI) based on the InterViews
    toolkit.  Allows user-selected "look and feel".

  o Network Viewer shows network architecture and processing in real-
    time, allows network to be constructed with simple point-and-click
    actions.

  o Training and testing data can be graphed on-line and network state
    can be displayed over time numerically or using a wide range of
    color or size-based graphical representations.

  o Environment Viewer shows training patterns using color or 
    size-based graphical representations; interactive configuration.

  o Flexible object-oriented design allows mix-and-match simulation
    construction and easy extension by deriving new object types from
    existing ones.

  o Built-in 'CSS' scripting language uses C++ syntax, allows full
    access to simulation object data and functions.  Transition
    between script code and compiled code is simplified since both are
    C++. Script has command-line completion, source-level debugger,
    and provides standard C/C++ library functions and objects.

  o Scripts can control processing, generate training and testing
    patterns, automate routine tasks, etc.

  o Scripts can be generated from GUI actions, and the user can create 
    GUI interfaces from script objects to extend and customize the
    simulation environment.


Supported Algorithms:
=====================

  o Feedforward and recurrent error backpropagation.  Recurrent BP
    includes continuous, real-time models, and Almeida-Pineda.

  o Constraint satisfaction algorithms and associated learning
    algorithms including Boltzmann Machine, Hopfield models,
    mean-field networks (DBM), Interactive Activation and
    Competition (IAC), and continuous stochastic networks.

  o Self-organizing learning including Competitive Learning, Soft
    Competitive Learning, simple Hebbian, and Self-organizing Maps
    ("Kohonen Nets").

  o Leabra algorithm that combines error-driven and Hebbian learning
    with k-Winners-Take-All inhibitory competition.  Over 40
    research-grade simulations available for this algorithm in
    association with new book: "Computational Explorations in
    Cognitive Neuroscience: Understanding the Mind by Simulating the
    Brain", O'Reilly & Munakata, 2000, MIT Press.