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Andy Wuensche andy AT ddlab DOT org |
Visiting research fellow Dept. of Informatics (formerly COGS) School of Science and Technology, University of Sussex
Visiting Professor |
DDLab mirror sites: www.sussex.ac.uk/Users/andywu/ddlab.html uncomp.uwe.ac.uk/wuensche/ddlab.html www.ddlab.org |
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pencil drawing from the very early days before automatic computer drawing was perfected |
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Exploring Discrete Dynamics - Second Edition
(EDD2)
is published by Luniver Press. EDD2 is a 8x10 inch 577 page paperback with color figures, and can be purchased
at
Amazon-UK,
Amazon-USA, and other online book sellers. The hyperref-pdf file (24 MB) is also
available and can be downloaded
HERE. EDD2 is fully compatible with the latest versions of DDLab.
Advance Praise by Stuart Kauffman |
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Update June 2016 DDLabz04 Recent UPDATES include rescaling transients (#25.2.2), network wiring using the mouse (chapter 17), save/load seeds following the Golly format (#21.11), and many other new features. Feedback to: andy AT ddlab DOT org
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 rescaling transients |
 3d reaction-diffusion 44-cube |
 "bare" attractor (Life glider-gun) |
density plot, v3k6 |
 glider time-trails
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| ddlab_compiled_2016 | compiled ddlabz04, 64-bit for Linux and Mac.
32-bit for Linux, Mac, Cygwin and DOS.|
ddlab_code_2016
| source code for ddlabz04, including
Makefiles and readme |
download directory
| for the above, and
Exploring Discrete Dynamics-SecondEdition.pdf (EDD2),
dd_extra.tar.gz
extra files
to supplement DDLab (EDD section 3.6),
and
fonts_dd_linux.tar.gz
fonts for Linux which may be required.
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Uninversity of Sussex
| University of the West of England
Mirror sites for all versions of DDLab, code, and documentation,
including the latest, dating back 1995.
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sourceforge
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Open Source software repository of recent versions of DDLab, code, and documentation.
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 3d glider-gun click to enlarge |
 The Spiral Rule |
 1d CA space-time pattern present- ed as a scrolling tube. The pres- ent moment is at the front |
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Null Bpoundary Conditions, Basin of attraction field, ECA rule 150, n=11 |
 3d 200x200x200 space-time patt- ern. Large sizes are possible in ddlabx09 |
DDLab is free (open source) software under the GNU General Public License.
However, institutional users (commercial or educational) are required to register
and pay a registration fee. Personal users are also encouraged to register.
Registered users will receive a simple instruction to remove the annoying
"UNREGISTERED" banners in DDLab. For registration details, click
HERE.
The figure on the right shows a new way of representing
a network as a graph which can be rearranged by dragging vertices.
This is a "scale free" RBN, n=150
with a power-law distribution of both k and out-degree. DDLab is interactive graphics software for researching discrete
dynamical networks, relevant to the study of complexity, emergent
phenomena, and neural and bio-molecular networks - especially
gene regulatory networks.
A discrete dynamical network can have arbitrary connections
and heterogeneous rules, and includes Cellular Autamata (CA),
and "Random Boolean Networks" (RBN), where the
"Boolean" atribute is extended to multi-value.
Lattice dimensions can be 1d, 2d (hex or square) or 3d.
Many tools and functions are available for creating the network
(its rules and wiring), setting the initial
state, analyzing the dynamics, and amending parameters on-the-fly.
An overview of DDLab and what it can do is provided in
this pdf preprint.
The program iterates the network forward to display space-time patterns,
and also runs the network "backwards" to generate a pattern's
predecessors and reconstruct its branching sub-tree of all ancestor patterns.
For smaller networks, sub-trees, basins of attraction or the whole basin
of attraction field can be reconstructed and displayed as
directed graphs in real time.
The DDLab
Gallery shows examples.
The network's parameters, and the graphics display and presentation
options, can be flexibly set, reviewed and altered, including changes
on-the-fly.
A wide variety of measures, data, analysis and statistics are available.
Learning/forgetting algorithms allow "sculpting" attractor basins
to approach a desired scheme of hierarchical categorization.
The DDLab
Gallery
The DDLab
Gallery
is a collection of DDLab images and graphics, with captions,
illustrating some of DDLab's features.
The Gallery was started in Oct 1998.
It will be continually added to and updated.
A similar graph is the "attractor jump-graph",
which shows the probability of jumping between basins of attraction
subject to noise. For some examples
click here
Lecture slides
About 80 of my lecture slides that have accumulated since 2006.
Click here to see the slide pdf file
in a new window - its a large file so might take a minute.
You may use/copy these slides provided you reference myself and DDLab.
Attractor Basins
Attractor basins of discrete dynamical networks are objects in
space-time that link network states according to their
transitions. Click
here for a summary of idea.
Access to these objects provides insights into complexity,
chaos and emergent phenomena in cellular automata. In less ordered
networks (as well as CA), attractor basins show how a network is able to
categorize its state space, explaining what it is that constitutes
memory in a network.
What is DDLab?
1d scrolling space-time patterns
Reviews
Reviews of DDLab
Reviews of
"The Global Dynamics of
Cellular Automata", by Andrew Wuensche and Mike Lesser.
The entire book has been scanned and is available in
pdf -- 39,09M.
Reviews of
Exploring Discrete Dynamics by Andrew Wuensche.
DDLab's screen saver -- click to enlarge
Related Publications
Books and various papers related to DDLab are
listed
here, most are in pdf.
back to the start of DDLab
Last modified: June 2016