From alife@COGNET.UCLA.EDU Mon Apr  5 23:37:32 1993
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Date: Fri, 26 Mar 93 18:11:53 -0800
From: alife@COGNET.UCLA.EDU
Message-Id: <9303270211.AA01031@regulus.cognet.ucla.edu>
To: alife@COGNET.UCLA.EDU
Subject:  Alife Digest Volume #097
Status: R

                       Alife Digest, Number 097
                       Friday, March 26th 1993

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
~                   Artificial Life Distribution List                     ~
~                                                                         ~
~        All submissions for distribution to: alife@cognet.ucla.edu       ~
~ All list subscriber additions, deletions, or administrative details to: ~
~                      alife-request@cognet.ucla.edu                      ~
~         All software, tech reports to Alife depository through          ~
~  anonymous ftp at ftp.cognet.ucla.edu in ~ftp/pub/alife (128.97.50.19)  ~
~                                                                         ~
~             List maintainers: Liane Gabora and Rob Collins              ~
~                  Artificial Life Research Group, UCLA                   ~
~                                                                         ~
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Today's Topics:

                   Calendar of Alife-related Events
                           Paper Available
           Emergent Robot Behavior using Classifier Systems
              Nonlinear Science Preprint Bulletin Board
                Announcing the hodge-podge machine...
                 Animal Behaviour Software Available
             Announcement of Availability of CA software
                Evolutionary Robotics - Tech. Reports

----------------------------------------------------------------------

Date: Fri, 26 Mar 93 18:05:36 -0800
From: liane@CS.UCLA.EDU (Liane Gabora)
Subject: Calendar of Alife-related Events

 **********************************************************************

Conf on Fuzzy Systems, San Francisco CA                 Mar 28-Apr 1, 1993 v79
AI and Simulation of Behaviour Conf, Birmingham UK      Mar 29-Apr 2, 1993 v75
Intnl Conf on Neural Nets and GAs, Innsbruck, Austria   Apr 13-16, 1993    v80
BEAM Robot Olympics, Toronto Canada                     Apr 22-25, 1993    v81
Workshop On Computational Neurosciences, Austin, TX     May 14-15, 1993    v94
European Conf on ALife, Brussels                        May 24-26, 1993    v82
Intnl Workshop Neural Networks, Barcelona Spain         June 9-11, 1993    v76
World Congress on Neural Networks, Portland, OR         July 11-15, 1993   v95
Intelligent Systems for Molecular Biology, Washington   July 7-9, 1993     v84
Fifth Intnl Conf on GAs, Urbana-Champaign IL            July 17-22, 1993   v80
Dynamically Interacting Robots Workshop                 Late Aug, 1993     v91
Congress on Medical Informatics, Sao Paulo, Brazil      Sept 9-14, 1995    v91

 (Send announcements of other activities to alife@cognet.ucla.edu)

 **********************************************************************

------------------------------

Date: Wed, 17 Mar 93 15:55:31 MST
From: mm@santafe.edu
Subject: Paper Available

The following paper is available by public ftp.

		      Revisiting the Edge of Chaos: 
	    Evolving Cellular Automata to Perform Computations
	
   Melanie Mitchell       Peter T. Hraber         James P. Crutchfield
  Santa Fe Institute    Santa Fe Institute  University of California, Berkeley

              Santa Fe Institute Working Paper 93-03-014

                                Abstract

We present results from an experiment similar to one performed by
Packard (1988), in which a genetic algorithm is used to evolve 
cellular automata (CA) to perform a particular computational task.  Packard
examined the frequency of evolved CA rules as a function of Langton's 
lambda parameter (Langton, 1990), and interpreted the results of his 
experiment as giving evidence for the following two hypotheses:
(1) CA rules able to perform complex computations are most likely
to be found near ``critical'' lambda values, which have been claimed
to correlate with a phase transition between ordered and chaotic behavioral
regimes for CA;  (2) When CA rules are evolved to perform a complex
computation, evolution will tend to select rules with lambda values
close to the critical values.   Our experiment produced very different results,
and we suggest that the interpretation of the original results is not 
correct.  We also review and discuss issues related to lambda, 
dynamical-behavior classes, and computation in CA.  

The main constructive results of our study are identifying the emergence 
and competition of computational strategies and analyzing the central
role of symmetries in an evolutionary system. In particular, we
demonstrate how symmetry breaking can impede the evolution toward
higher computational capability.

To obtain an electronic copy:

	ftp santafe.edu
	login: anonymous
	password: <your email address>
	cd /pub/Users/mm
	binary
	get rev-edge.ps.Z 
	quit

Then at your system:

	uncompress rev-edge.ps.Z
	lpr -P<printer-name> rev-edge.ps

To obtain a hard copy, send a request to mm@santafe.edu.  

------------------------------

From: A.Fraser@eee.salford.ac.uk
Date: 19 Mar 93 14:46
Subject: Emergent Robot Behavior using Classifier Systems

At Salford University, within the Mobile Robots Research Group, we are
attempting to develop classifier systems which will produce emergent
behaviours for the control of mini-mobots.  While some work has
already been done with neural networks (see Randall Beers ,
Intelligence as Adapative Behaviour: An Investigation into
Computational Neuroethology) we feel the abilty to be able to evolve
new behaviours is necessary.  In the near future we can envisage
complex tasks being asked of a number of mobile robots which will then
use genetic algorithms to evolve, from maybe a base of initial
behaviours or a completely blank behavioural base, the behaviours
needed to complete the task.

Our initial forays into classifier systems have been to try and
re-implement UCLA's Santa Fe (or John Muir) trail where an artificial
insect attempts to follow a pheremone trail with progressively more
complex turns (see D.Jefferson et al Artificial Life II and J.Koza
Artificail Life II). We are also looking into learning in classifier
systems which will be applied in such a way that a robotic device can
adapt on-line to a dynamic environment.  While implementing such
systems we have come across problems not discussed in papers such as:
should a classifier, which is created by a random function, be able to
have a large number of possible conditions linked by logical operators
and if so how?

If anyone has tried to implement a classifier (preferably, but not
necessarily in C++) and has any advice to give then please e-mail us.
Also if anyone is working in the field of evolutionary robotics (see
Alife Digest 94) we would be pleased to hear from you.

Thanks in advance....

          Adam P.Fraser     John R. Rush

=============================================================================
|| ||\\   /|| ||\\    ||\\     //\\    || A.P.Fraser,                      ||
|| || \\ / || ||  \\  ||  \\  //       || Snail:PostGraduate Section       ||
|| ||   /  || ||  //  ||  // //   \\\  ||       Elec & Electronic Dept     ||
|| ||      || ||//\   ||//\   \\   //  ||       University Of Salford      ||
|| ||      || ||   \\ ||   \\   \\//   ||       Salford, M5 4WT, England   ||
|| ...Mobile Robots Research Group...  || Email:A.Fraser@eee.salford.ac.uk ||
=============================================================================
||||        When we try to pick anything out by itself,  we find         ||||
||||    it hitched to everything else in the universe.  - John Muir      ||||
=============================================================================

------------------------------

Date: Fri, 19 Mar 93 21:28:36 MST
From: erica@huoshan.lanl.gov (Ren Jun-Rui)
Subject: Nonlinear Science Preprint Bulletin Board

{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}
{*}+                                                               +{*}
{*}+                     NONLINEAR SCIENCE                         +{*}
{*}+                PREPRINT BULLETIN BOARD (PBB)                  +{*}
{*}+                                                               +{*}
{*}+                     Coordinated by the                        +{*}
{*}+             Center for Nonlinear Studies (CNLS)               +{*}
{*}+          Software developed by Theoretical Division           +{*}
{*}+               Los Alamos National Laboratory                  +{*}
{*}+                                                               +{*}
{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}

An electronic Nonlinear Science Preprint Bulletin Board (PBB) has been
established as of March 5, 1993.  

The PBB provides a fully automated system for the archiving and distribution 
of electronic preprints.  Preprints are submitted electronically to the system,
which assigns them reference numbers, and makes them available to PBB users
via a wide variety of conventional means of network access.  The simplest such
access is via e-mail request, through which remote users may, for example, get 
help on available commands, obtain the full texts of papers, obtain listings
for given periods, and search for author names or keywords. The system allows
the original submitter of a paper to incorporate ongoing corrections and
addenda (and adds an entry to the daily listings with an author supplied
synopsis of any changes).  The system also permits anonymous FTP access to 
papers and macros stored in the data base, as well as access by other rapidly
developing network utilities such as WAIS, Gopher, and WorldWideWeb.  
A cross-referencing feature is available to establish linkages among bulletin 
boards in different disciplines. 

All researchers in the nonlinear science community are invited to submit 
electronic preprints to the Nonlinear Science PBB.  For purposes of 
standardization, users are encouraged, albeit not required, to submit text 
in TeX or LaTeX format, with figures in uuencoded tar-compressed postscript 
files.  (If necessary, papers may also be submitted with a note indicating 
that non-electronic figures are to be obtained directly from the authors.)
PBB subscribers are notified regularly by e-mail of new submissions. 
Listings, retrievals, and searches of preprints may be performed at any 
time without subscribing to the regular mailing service.  Usage of the 
PBB is free of charge.

The nonlinear science PBB is divided into the following categories:

CATEGORY                     INTERNET ADDRESS         ADVISORS

dynamical systems/chaos/     chao-dyn@xyz.lanl.gov    Predrag Cvitanovich
 quantum chaos/topological                            Mitchell Feigenbaum 
 dynamics/cycle expansions                            John Guckenheimer 
 turbulence/propagation                               Ronnie Mainieri 
                                                      Jerrold Marsden
                                                      Michael Tabor  

pattern formation/coherent   patt-sol@xyz.lanl.gov  * Guenter Ahlers  
 structures/integrable                                Alan Bishop
 systems/solitons                                     David Campbell
                                                      Sue Coppersmith
                                                      Irving Epstein
                                                      Alan Newell

adaptation/interacting       adap-org@xyz.lanl.gov    Phil Anderson
 particle systems/self-                               James Crutchfield
 organizing systems/                                  David Griffeath 
 computation theory/                                  Charles Taylor
 machine learning                                     Jordan Pollack
                                                      Daniel Stein

computational methods/time   comp-gas@xyz.lanl.gov  * Gregory Beylkin  
 series analysis/signal                               Gary Doolen
 processing/wavelets/lattice                          James Glimm 
 gases                                                Brosl Hasslacher
                                                      James M. Hyman 
                                                      George Zweig

[all of the above]           nlin-sys@xyz.lanl.gov    Erica Jen

                                                    * unconfirmed

Users may access and/or subscribe to any subset of the above categories, 
or to nlin-sys which contains the entire data base; preprints should 
however be submitted to only a single category since cross-linkage 
options, as explained in the documentation for any of the categories, 
eliminate the need for multiple storage.  

Information on usage of the PBB may be obtained by sending an e-mail 
message with the subject "help" and a blank message body to any of the 
above internet addresses; e.g..

To: nlin-sys@xyz.lanl.gov
Subject:  help

Included in the "help" documentation are instructions for the use of 
other commands: 

  subscribe  get    put    listing       cross      replace 
  cancel     add    find   distribution  published  comment 

typically invoked, as in the case of "help,"  by sending e-mail to the proper 
internet address with a subject consisting of the command and requisite 
arguments, together with a message body where appropriate. To subscribe to 
the full nlin-sys, for example, send e-mail with a blank message body

To: nlin-sys@xyz.lanl.gov
Subject:  subscribe [your name] 

replacing [your name] by your full name (spaces and initials allowed) as 
you wish it to appear in the distribution list.  Preprint notifications
will then be sent to the e-mail address from which you subscribed.  Any 
of the categories [chao-dyn patt-sol adap-org comp-gas] may be substituted 
for nlin-sys if you wish to subscribe only to that subset.

PBBs currently in operation in other disciplines, utilizing the same 
software and to which cross-linkages are operative, include:

alg-geom@publications.math.duke.edu  (algebraic geometry)
astro-ph@babbage.sissa.it            (astrophysics)
cond-mat@babbage.sissa.it            (condensed matter)
e-mail@xxx.lanl.gov                  (e-mail address database)
funct-an@babbage.sissa.it            (functional analysis)
gr-qc@xxx.lanl.gov                   (gravitation, quantum cosmology)
nucl-th@xxx.lanl.gov                 (nuclear physics, theory)
hep-lat@ftp.scri.fsu.edu             (computational and lattice physics)
hep-ph@xxx.lanl.gov                  (high energy physics, phenomenological)
hep-th@xxx.lanl.gov                  (high energy physics, formal)

A list is also being compiled of other electronic preprint systems (based on 
other software) in all scientific disciplines.  At present the list includes:

mp_arc@math.utexas.edu               (mathematical physics preprints)
cycler@goshawk.lanl.gov              (cycle expansions preprints)
csp2.csp.uga.edu  [128.192.19.229]   (simulational physics FTP server)

If you know of other such systems, please send e-mail as a "comment"

To:  nlin-sys@xyz.lanl.gov
Subject:  comment 

describing the scope of the system, its internet address, and "help" 
instructions.  Comments on nlin-sys may also be sent to the above address 
or to any of the category addresses, and will be forwarded if appropriate 
to the scientific advisors.

A copy of this announcement is obtainable by sending e-mail 

To: nlin-sys@xyz.lanl.gov
Subject:  get announce 

{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}
{*}+                    revised 1993.3.12                          +{*}
{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}+{*}

------------------------------

From: Joerg Heitkoetter <heitkoet@lusty.informatik.uni-dortmund.de>
Date: Sat, 20 Mar 93 16:58:36 +0100
Subject: Announcing the hodge-podge machine...

Enclosed the README file  of  HODGE-C,  a  cellular-automata
simulator.

HODGE-C:
--------

HODGE-C is  a  (`mostly  ANSI')  C  language  implemenatation  of
Gerhard  &  Schuster's hodge-podge machine. It implements a class
of cellular automata, that resemble  very  closely  autocatalytic
chemical  reactions,  like for example, the Belousov-Zhabotinskii
(BZ) reaction. It's main purpose is given in  the  following  ex-
cerpt from the manual page:

ANIMATION
     hodge's main purpose is to generate the previously mentioned
     snapshot files for `making movies'.  All you need is, eg. E.
     I. du Pont de Nemours & Company's  ImageMagick  PD  software
     (available  via  anonymous  ftp  from export.lcs.mit.edu, as
     file `contrib/ImageMagick.tar.Z.') using the package's  ani-
     mate(1)  command  you'll  soon  see BZ waves move across the
     grid.  An example for  this  is  given  in  the  hodge/movie
     folder of the HODGE-C distribution.

     A different approach is to use IDL  from  Research  Systems,
     Inc.  Boulder, CO, USA. An example for this purpose is given
     in the hodge/idl folder of the HODGE-C distribution.

     An animation companion to pixmon(1)  called  playmate(1)  is
     also  in  the making, and will be distributed in near future
     (refer to the AVAILABILITY section below).  Its  application
     is  rather simple: all there is to do is to include a ``tee-
     log'' in the `--monitor-process' eg.:

     --monitor-process 'tee >pmdata.pix | pixmon ...'

     to  collect  pixmon(1)  data,  that  is  later  turned  into
     animated pixmaps by playmate(1).

     A final, powerful and low cost solution for animation is  to
     install  the KHOROS visualization package on your system. It
     comes for free from the University of  New  Mexico,  and  is
     better  than most commercial products.  KHOROS also features
     an easy to use graphical programming interface  called  CAN-
     TATA  and  is very easy to learn for beginners in scientific
     visualization. KHOROS features a bunch of converters to it's
     internal  VIFF(5)  format,  that  is  easily  generated from
     hodge's dump (eg. asc2viff(1)) and animation data files (eg.
     pbm2viff(1), rast2viff, raw2viff(1), etc.) [..]

For an introductory article  on  hodge-podge  see:  A.K.Dewdney's
Computer Recreations column, in Scientific American, August 1988.

HODGE-C is distributed free of charge and the other terms of  the
GPL, ie.  the GNU General Public License.

HODGE-C v0.98j is available via  ftp  from  lumpi.informatik.uni-
dortmund.de  (129.217.36.140).   Log  on with user name "ftp" and
give your full e-mail address as  password.   The  file  hodge-c-
0.98j.tar.Z   in  directory  /pub/CA/src  contains  the  complete
software and documentation.

HODGE-C v0.98j was  posted  to  comp.sources.misc,  and  thus  is
available  from  every newsarchive server close to you.  (In Ger-
many   ftp   to    ftp.germany.eu.net,    and    see    directory
/pub/newsarchive/comp.sources.misc)

For more information contact:

	Joerg Heitkoetter
	(joke@ls11.informatik.uni-dortmunde.de)

    c/o Systems Analysis Group, LSXI
	Department of Computer Science             ////
	University of Dortmund                UNI DO// 
	P.O. Box 500 500                     ___ ////
	4600 Dortmund 50                     \*\\///
	Germany                               \\\\/

------------------------------

Date: Mon, 22 Mar 93 19:23:10 GMT
From: Toby Tyrrell <lrtt@cns.edinburgh.ac.uk>
Subject: Animal Behaviour Software Available

            PhD dissertation and simulation software available
                    [instructions at end of message]

DISSERTATION.

Imagine a zebra in the African savannah.  At each moment in time this zebra
has to weigh up alternative courses of action before deciding which one will
be most beneficial.  For instance, it may want to graze because it is short
of food, or it may want to head towards a water hole because it is short of
water, or it may want to remain motionless in order to avoid detection by
the predator lurking nearby.  This is an example of the problem of action
selection: how to choose, at each moment in time, the most appropriate out
of a repertoire of possible actions.

This thesis investigates action selection in a novel way and makes three
main contributions.  Firstly, a description is given of a simulated
environment which is an extensive and painstaking simulation of the problem
of action selection for animals.  Secondly, this complex simulated
environment is used to investigate the adequacy of several theories of
action selection (from both ethology and artificial intelligence) such as
the drive model, Lorenz's psycho-hydraulic model and Maes' spreading
activation network - deficiencies in all of these mechanisms were discovered
and their implications are outlined. Thirdly, a new approach to action
selection is developed which determines the most appropriate action in a
principled way, and which does not suffer from the inherent shortcomings
found in other methods.

A review and bibliography of existing work on action selection is included.

To obtain the thesis:

1 - "ftp ftp.ed.ac.uk"			(129.215.146.5)
2 - user name = "anonymous", password = your user name
3 - "binary"
4 - "cd pub/lrtt"
5 - "get as.1.ps.Z", "get as.2.ps.Z" .... "get as.7.ps.Z"
6 - "quit"
and then "uncompress as.1.ps.Z".  The postscript file can then be previewed
(e.g. "ghostview as.1.ps") or printed (e.g. "lpr -Plw as.1.ps").  Similarly
for the other 6 parts.

SIMULATION SOFTWARE.

This was written in Suntools rather than Xtools.  It can be run only from
SunView or OpenWindows.  The action selection problem modelled by the
simulated environment comprises 15 different `sub-problems' (getting food,
reproducing, not getting lost, being vigilant for predators, etc), many
internal and external stimuli, and 35 different low-level actions to select
between.

To obtain the software:

1 - "ftp ftp.ed.ac.uk"          (129.215.146.5)
2 - user name = "anonymous", password = your user name
3 - "binary"
4 - "cd pub/lrtt"
5 - "get se.tar.Z"
6 - "quit"
and then to install it "uncompress se.tar.Z ; tar xvf se.tar" and follow the
instructions in as/README.

------------------------------

Date: Tue, 23 Mar 93 14:39:00 -0500
From: hhchou@cs.UMD.EDU (Hui-Hsien Chou)
Subject: Announcement of Availability of CA software

         Simple Systems Exhibiting Self-Directed Replication:
          Transition Functions, Software, and Documentation
                          March, 1993

We have recently developed and studied cellular automata models of
self-replicating systems [Science, 259, 1993, pp. 1282-1288].  
Files containing a version of the various transition functions 
and software that we used in this study, as well as documentation, 
are now available via ftp.  The cellular automata software is actually 
fairly general and could also serve as an application-independent 
simulator.  For further details please refer to the paper cited above.

Here is a brief description of how to get this online information:

1. If your system is not on Internet we cannot help. You might
   ask your friends on Internet to get this material for you.

2. If you are on Internet, type

	ftp ftp.cs.umd.edu

   if this does not work, type

	ftp 128.8.128.8

   You will see the following message

	Connected to 128.8.128.8.
	220 mimsy.cs.umd.edu FTP server (Version 4.135 Thu Apr 26...
	Name (128.8.128.8:hhchou): 

   Now type in the login name "anonymous", then type in your email id
   as the password. You will see the following prompt

	Name (128.8.128.8:hhchou): anonymous
	331 Guest login ok, send ident as password.
	Password:
	230 Guest login ok, access restrictions apply.
	ftp> 

3. Type the following command to change directory to /pub

	cd pub

   Next type the following command to signify binary file transfer

	bi

   You will see the following message

	ftp> cd pub
	250 CWD command successful.
	ftp> bi  
	200 Type set to I.
	ftp>

4. Next, type the following command to get the files.

	get dtr.tar.Z

   You will see something like this

	ftp> get dtr.tar.Z
	200 PORT command successful.
	150 Opening data connection for dtr.tar.Z (128.8.128.151,...
	226 Transfer complete.
	local: dtr.tar.Z remote: dtr.tar.Z
	1598529 bytes received in 49 seconds (32 Kbytes/s)
	ftp> 

   Type the following command to quit ftp

	quit

5. After you have transferred the files, move them somewhere in your
   system where you want to store them. Finally, type

	zcat dtr.tar.Z | tar xvf -

   This will retrieve everything in this package, and give you a
   directory called "dtr". Follow the instructions in the README file
   there. 

We hope you find this package useful to you. Note that although care
has been taken while preparing this package, we know bugs are there
somewhere. We do not have the resources to provide maintenance and 
support for this software.  Suggestions or bug reports are welcome.  
If time permits we will try to fix any bug found and provide an improved
version in the future.  We would appreciate it if you acknowledge the
use of this software in any future research reports that you might
base upon it and send us a copy of such reports.

Please send your correspondence to:
     hhchou@eng.umd.edu.

Hui-Hsien Chou
Dept. of Computer Science
A.V. Williams Bldg.
University of Maryland at College Park
College Park, MD 20742 USA

------------------------------

From: Inman Harvey <inmanh@cogs.sussex.ac.uk>
Date: Wed, 24 Mar 93 10:17:28 GMT
Subject: Evolutionary Robotics - Tech. Reports

Evolutionary Robotics at Sussex -- Technical Reports
===============================

The following six technical reports describe our recent work in using genetic
algorithms to develop neural-network controllers for a simulated simple
visually-guided robot.

Currently only hard-copies are available. To request copies, mail one of:
inmanh@cogs.susx.ac.uk or davec@cogs.susx.ac.uk or philh@cogs.susx.ac.uk
giving a surface mail address and the CSRP numbers of the reports you want.

or write to us at:
School of Cognitive and Computing Sciences
University of Sussex
Brighton BN1 9QH
England, UK.

------------ABSTRACTS--------------------

Genetic convergence in a species of evolved robot control architectures
I. Harvey, P. Husbands, D. Cliff
Cognitive Science Research Paper CSRP267
February 1993
We analyse how the project of evolving 'neural' network controller for
autonomous visually guided robots is significantly different from the usual
function optimisation problems standard genetic algorithms are asked to
tackle.  The need to have open ended increase in complexity of the
controllers, to allow for an indefinite number of new tasks to be
incrementally added to the robot's capabilities in the long term, means that
genotypes of arbitrary length need to be allowed. This results in
populations being genetically converged as new tasks are added, and needs a
change to usual genetic algorithm practices. Results of successful runs are
shown, and the population is analysed in terms of genetic convergence and
movement in time across sequence space.

Analysing recurrent dynamical networks evolved for robot control
P. Husbands, I. Harvey, D. Cliff
Cognitive Science Research Paper CSRP265
January 1993
This paper shows how a mixture of qualitative and quantitative analysis can
be used to understand a particular brand of arbitrarily recurrent continuous
dynamical neural network used to generate robust behaviours in autonomous
mobile robots.  These networks have been evolved in an open-ended way using an
extended form of genetic algorithm.  After briefly covering the background to
our research, properties of special frequently occurring subnetworks are
analysed mathematically. Networks evolved to control simple robots with low
resolution sensing are then analysed, using a combination of knowledge of
these mathematical properties and careful interpretation of time plots of
sensor, neuron and motor activities.

Analysis of evolved sensory-motor controllers
D. Cliff, P. Husbands, I. Harvey
Cognitive Science Research Paper CSRP264
December 1992
We present results from the concurrent evolution of visual sensing
morphologies and sensory-motor controller-networks for visually guided robots.
In this paper we analyse two (of many) networks which result from using
incremental evolution with variable-length genotypes. The two networks come
from separate populations, evolved using a common fitness function. The
observable behaviours of the two robots are very similar, and close to the
optimal behaviour. However, the underlying sensing morphologies and
sensory-motor controllers are strikingly different. This is a case of
convergent evolution at the behavioural level, coupled with divergent
evolution at the morphological level. The action of the evolved networks is
described. We discuss the process of analysing evolved artificial networks, a
process which bears many similarities to analysing biological nervous systems
in the field of neuroethology.

Incremental evolution of neural network architectures for adaptive behaviour
D. Cliff, I. Harvey, P. Husbands
Cognitive Science Research Paper CSRP256
December 1992
This paper describes aspects of our ongoing work in evolving recurrent
dynamical artificial neural networks which act as sensory-motor controllers,
generating adaptive behaviour in artificial agents. We start with a discussion
of the rationale for our approach. Our approach involves the use of recurrent
networks of artificial neurons with rich dynamics, resilience to noise (both
internal and external); and separate excitation and inhibition channels. The
networks allow artificial agents (simulated or robotic) to exhibit adaptive
behaviour. The complexity of designing networks built from such units
leads us to use our own extended form of genetic algorithm, which allows for
incremental automatic evolution of controller-networks. Finally, we review
some of our recent results, applying our methods to work with simple
visually-guided robots. The genetic algorithm generates useful network
architectures from an initial set of randomly-connected networks. During
evolution, uniform noise was added to the activation of each neuron. After
evolution, we studied two evolved networks, to see how their performance
varied when the noise range was altered. Significantly, we discovered that
when the noise was eliminated, the performance of the networks degraded: the
networks use noise to operate efficiently.

Evolving visually guided robots
D. Cliff, P. Husbands, I. Harvey
Cognitive Science Research Paper CSRP220
July 1992
We have developed a methodology grounded in two beliefs: that autonomous
agents need visual processing capabilities, and that the approach of
hand-designing control architectures for autonomous agents is likely to be
superseded by methods involving the artificial evolution of comparable
architectures. In this paper we present results which demonstrate that
neural-network control architectures can be evolved for an accurate simulation
model of a visually guided robot. The simulation system involves detailed
models of the physics of a real robot built at Sussex; and the simulated
vision involves ray-tracing computer graphics, using  models of optical
systems which could readily be constructed from discrete components. The
control-network architecture is entirely under genetic control, as are
parameters governing the optical system. Significantly, we demonstrate that
robust visually-guided control systems evolve from evaluation functions which
do not explicitly involve monitoring visual input. The latter part of the
paper discusses work now under development, which allows us to engage in
long-term fundamental experiments aimed at thoroughly exploring the
possibilities of concurrently evolving control networks and visual sensors for
navigational tasks. This involves the construction of specialised
visual-robotic equipment which eliminates the need for simulated sensing.

Issues in evolutionary robotics
I. Harvey, P. Husbands, D. Cliff
Cognitive Science Research Paper CSRP219
July 1992
In this paper we propose and justify a methodology for the development of
the control systems, or `cognitive architectures', of autonomous mobile
robots. We argue that the design by hand of such control systems becomes
prohibitively difficult as complexity increases. We discuss an alternative
approach, involving artificial evolution, where the basic building blocks for
cognitive architectures are adaptive noise-tolerant dynamical neural networks,
rather than programs. These networks may be recurrent, and should operate in
real time. Evolution should be incremental, using an extended and modified
version of genetic algorithms. We finally propose that, sooner rather than
later, visual processing will be required in order for robots to engage in
non-trivial navigation behaviours. Time constraints suggest that initial
architecture evaluations should be largely done in simulation. The pitfalls of
simulations compared with reality are discussed, together with the importance
of incorporating noise. To support our claims and proposals, we present
results from some preliminary experiments where robots which roam office-like
environments are evolved.

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End of ALife Digest
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