X-Message-Number: 6144
Date: Mon, 6 May 1996 16:34:47 +0200 (MET DST)
From: Eugene Leitl < var s1 = "Eugene.Leitl"; var s2 = "lrz.uni-muenchen.de"; var s3 = s1 + "@" + s2; document.write("<a href='mailto:" + s3 + "'>" + s3 + "</a>"); >
Subject: rant warning

("bandwidth? which bandwidth??? anybody seen my bandwith
somewhere?" -- Apologies are due to these still under fell
dominion of grim feudalistic providers -- but then, it's their
own fault. Mailbombing can sometimes be fun -- from the right
side of the mailer, that is. Signed: member of the anonymous
witzelsucht victim circle).
_________________________________________________________________

by way of explanation... "ask not what the web can do for you --
ask what you can do for the web"
_________________________________________________________________

"everything is deeply intertwingled" -- Wise guy, eh?
_________________________________________________________________

It's not quite easy hunting up books with a bright >H streak. It
turns out to be quite time-consuming and is not exactly cheap,
either. Fortunately (?), most people tend to buy really shallow
treekiller trash while letting the true gems gathering dust in
the bookshelves, to be chucked out for cheap after a year or
two. (I just hope the dealers won't wise up too soon and drop
acquiring them altogether). As so often in life, it quite pays
out playing the vulture bit and letting the delicious roadkill
cure in the sun for a while -- it makes its fibres far more
tender and tends to give the juicy dish an interesting new
salivaent savvyoury flavour. You get slightly out of synch of
course, but so what. By taking the slow dusty road you might
encounter new landmarks the numerous shockwave riders failed to
notice as they roared by. "Tishe jedesh -- dal'she budesh."

Let's polish up some of the dusty gems.
_________________________________________________________________

Stephen Wolfram, "Cellular Automata and Complexity -- collected
papers", Addison Wesley (1994), 596 pp. (At this opportunity I'd
like to voice my extreme gratitude towards Stephen Wolfram (of
"Mathematica" (truly cool computer algebra software) fame), who
has snail-mailed (we _need_ 3d-nanolithography printers for
output periphery -- "amaze your friends and neighbours! fax six
pounds of plastique plus primer fuse right into their living
rooms!") a very noticeable number of its copies to his web fan
community for free. Watch out for his forthcoming "A New Kind of
Science", it will be certainly well worth the bucks).

This is a tasty chili potpourri to learn what CA is all about
and why it is universally unrivalledly considered to be so very
!HOT! . Though slightly outdated, this semicompleat Wolfram
(from "wolf-rahm" = wolf-foam, for tungsten ore "devouring" tin
in medieval cassiterite metallurgy) volume is extremely
readable, maths background involved is not very high and quite
varying, giving enough crunchy yummy entry points for any
reader. I hope nobody will lynch me (System message -- from:
sendicbm daemon: "warning: mail return-to-sender in progress due
to invalid GPS grid target") for embedding the abstracts, since
they are merely meant as an appetizer sweetmeats to sent people
running (lollying tongues flattering in the breeze) to their
bookstores while leaving trails of saliva in their tracks.
("Welcome, stranger. The paths are slippery tonight".)

A Note from the Publisher.

"The work of Stephen Wolfram in the early 1980s played a central
role in launching a new field of science concerned with the
problem of complexity. By now, Wolfram's work has been the basis
for thousands of papers in the scientific literature, as well as
for several popular books. Yet Wolfram's own original papers are
still some of the best sources.

These papers can, however, be somewhat difficult to obtain,
since they appear in journals from a wide variety of
disciplines. The purpose of this book is to make available a
complete collection of Wolfram's papers on cellular automata
and complexity. The papers have been retypeset to follow
a uniform format, but are otherwise unmodified. The graphics
are when possible reproduced in the orgininal form.

This book represents much of Wolfram's scientific output from
the period of 1982 to 1986. Wolfram cut short his work on
complexity in 1986 to concentrate on the development of
Mathematica. Recently, however, Wolfram has returned to the
study of complexity, and is now writing a major book entitled "A
Science of Complexity" {{ Rem. of the Aegyptian scribe slave: it
has been recently retitled "A New Kind of Science", send mail to
" var s1 = "info"; var s2 = "new-science.com"; var s3 = s1 + "@" + s2; document.write("<a href='mailto:" + s3 + "'>" + s3 + "</a>"); " to obtain partial satori }}, describing
the new discoveries he has made. "A Science of Complexity" will
don't count on that either, signed: the scribe}}

Part One: Primary Papers

Statistical Mechanics of Cellular Automata (1983).

"Cellular automata are used as simple mathematical models to
investigate self-organization in statistical mechanics. A
detailed analysis is given of "elementary" cellular automata
consisting of a sequence of sites with values 0 and 1 on a line,
with each site evolving deterministically in discrete time steps
according to definite rules involving the values of its nearest
neighbours. With simple initial configurations, the cellular
automata either tend to homogenous states or generate
self-similiar patterns with fractal dimensions c.a. 1.59 or c.a.
1.69. With "random" initial configurations, the irreversible
character of the cellular automaton evolution leads to several
self-organization phenomena. Statistical properties of the
structures generated are found to lie in two universality
classes, independant of the details of the initial state or the
cellular automaton rules. More complicated cellular automata are
briefly considered, and connections with dynamical systems
theory and the formal theory of computation are discussed".

Algebraic Properties of Cellular Automata (1984).

"Cellular automata are discrete dynamical systems, of simple
constructions but complex and varied behaviour. Algebraic
techniques are used to give an extensive analysis of the global
properties of a class of finite cellular automata. The complete
structure of state transition diagrams is derived in terms of
algebraic and number theoretical quantities. The systems are
usually irreversible, and are found to evolve through transients
to attractors consisting of cycles sometimes containing a large
number of configurations".

Universality and Complexity of Cellular Automata (1984).

"Cellular automata are discrete dynamical systems with simple
construction but complex self-organizing behaviour. Evidence is
presented that all one-dimensional cellular automata fall into
four distinct universality classes. Characterization of
structures generated in these classes are discussed. Three
classes exhibit behaviour analogous to limit points, limit
cycles and chaotic attractors. The fourth class is probably
capable of universal computation, so that properties of its
infinite time behaviour are undecidable".

Computation Theory of Cellular Automata (1984).

"Self-organizing behaviour in cellular automata is discussed as
a computational process. Formal languages theory is used to
extend dynamical systems theory descriptions of cellular
automata. The sets of configurations generated after a finite
number of time steps of cellular automaton evolution are shown
to form regular languages. Many examples are given. The sizes of
the minimal grammars for these languages provide measures of the
complexities of the sets. This complexity is usually found to be
non-decreasing with time. The limit sets generated by some
classes of cellular automata correspond to regular languages.
For other classes of cellular automata they appear to correspond
to more complicated languages. Many properties of these sets are
then formally non-computable. It is suggested that such
undecidability is common in these and other dynamical systems."

Undecidability and Intractability in Theoretical Physics (1985).

"Physical processes are viewed as computation, and the
terms of the difficulty of performing the corresponding
computations. Cellular automata are used to provide explicit
examples of various formally undecidable and computationally
intractable problems. It is suggested that such problems are
common in physical models, and some other potential examples are
discussed".

Two-Dimensional Cellular Automata (1985).

"A largely phenomenological study of two-dimensional cellular
automata is reported. Qualitative classes of behaviour similiar
to those in one-dimensional cellular automata are found. Growth
from simple seeds in two-dimensional cellular automata can
produce patterns with complicated boundaries, characterized by a
variety of growth dimensions. Evolution from disordered states
can give domains with boundaries that execute effectively
continuous motions. Some global properties of cellular automata
can be described by entropies and Lyapunov exponents. Others are
undecidable."

Origin of Randomness in Physical Systems (1985).

"Randomness and chaos in physical systems are usually attributed
to external noise. But it is argued here that eeven without such
random input, the intrinsic behaviour of many nonlinear systems
can be computationally so complicated as to seem random in all
practical experiments. This effect is suggested as the basic
origin of such phenomena as fluid turbulence."

Thermodynamics and Hydrodynamics of Cellular Automata (1985).

"Simple cellular automata which seem to capture the essential
features of thermodynamics and hydrodynamics are discussed. At a
microscopic level, the cellular automata are discrete
approximations to molecular dynamics, and show relaxation
towards equilibrium. On a large scale, they behave like
continuum fluids, and suggest efficient methods for hydrodynamic
simulation".

{{ I cannot help but to distinctly hear an "Also spake
Zarathustra" theme coming from somewhere -- scribe slave }}

Random Sequence Generation by Cellular Automata (1986).

"A 1-dimensional cellular automaton which generates random
sequences is discussed. Each site in the cellular automaton has
value 0 or 1, and is updated in parallel according to the rule
a'_i=a_{i-1} XOR (a_i OR a_{i+1}) (a'_i = (a_{i-1} + a_i+a_{i+1}
+ a_ia_{i+1} mod 2). Despite the simplicity of this rule, the
time sequences of site values that it yield seem to be
completely random. Theese sequences are analysed by a variety of
empirical, combinatorial, statistical, dynamical systems theory
and computation theory methods. An efficient random sequence
generator based on them is suggested".

Approaches to Complexity Engineering (1986).

"Principles for designing complex systems with specified forms
of behaviour are discussed. Multiple scale cellular automata are
suggested as dissipative dynamical systems suitable for tasks
such as pattern recognition. Fundamental aspects of the
engineering of such systems are characterized using computation
theory, and some practical procedures are discussed".

{{Wait.. Hush! Did you hear that, too?}}

Minimal Cellular Automaton Approximation to Continuum Systems
(1986).

(sorry, no abstractx)

Cellular Automaton Fluids: Basic Theory (1986).

"Continuum equations are derived for the large-scale behaviour
of a class of cellular automaton models for fluids. The cellular
automata are discrete analogues of molecular dynamics, in which
particles with discrete velocities populate the links of a fixed
array of sites. Kinetic equation for microscopic particle
distributions are constructed. Hydrodynamic equations are then
derived using the Chapman-Enskog expansion. Slightly modified
Navier-Stokes equations are obtained in two and three dimensions
with certain lattices. Viscosities and other transport
coefficients are calculated using the Boltzmann transport
equation approximation. Some corrections to the equations of
motion for cellular automaton fluis beyond the Navier-Stokes
order are given".

Part Two: Additional and Survey Papers

Cellular Automata (1983, no abstracs)

Computers in Science and Mathematics (1984).

"Computation offers a new means of describing and investigating
scientific and mathematical systems. Simulation by computer may
be the only way to predict how certain complicated systems
evolve."

Geometry of Binomial Coefficients (1984, no abtracts)

Twenty Problems in Theory of Cellular Automata (1985).

"Cellular automata are simple mathematical systems that exhibit
very complex behaviour. They can be considered as discrete dynamical
systems  or as computational systems. Progress has recently been
made in studying several aspects of them. Twenty central problems
that remain unsolved are discussed".

Cryptography with Cellular Automata (1986).

"This abstract discusses a stream cipher based on a simple
one-dimensional cellular automaton. The cellular automaton
consists of a circular register with N cells, each having
a value a_i equal to 0 or 1. [...]"

Complex System Theory (1988).

"Some approaches to the study of complex systems are outlined.
They are encompassed by an emerging field of science concerned
with the general analysis of complexity".

Cellular Automaton Supercomputing (1988).

"Many of the models now used in science and engineering are over
a century old. Most of them can be implemented on modern digital
discusses new basic models which are much more directly suitable
for digital computer simulation [...]".

Part Three: Appendices

Tables of Cellular Automaton Properties
Scientific Bibliography of Stephen Wolfram
Index
_________________________________________________________________

"Remember what your momma said -- ''Life'' is not a game".

"Blame St. Andreas -- it's all his Fault".
_________________________________________________________________
(this is a slightly refurbished nanoreview I once posted
somewhere)

I recently ran into a marvelous book. Its called "The
Origins of Order - self-organization and selection in evolution"
and was written by Stuart A. Kauffman. (Oxford University Press,
1993, 709 pp. ISBN 0-19-507951-5, paperback).

It makes several bold, but well-augmented claims which may have
distinctive impact upon a wide variety of sciences. Spontaneous
self-organisation and adaptation in complex systems, "edge of
chaos", the origin of life, (co)evolution, aspects of the
protein folding problem and embryonal morphogenesis machinery,
system dynamics, strange attractors in state spaces, etc. are
some of the topics it handles.

What Dawkins has only hinted at, Kauffman delivers in abundance.
This highly interdisciplinary book is shockfull with graphical
computer simulations results, mathematical derivations, tables,
figures and lucid scientific prosa. The average reader needs
only some high-school-level math, a dab of molecular biology and
certain amount of determination to wade through this enjoyable
tome.

It has been very favourably commented by such demigods of
science as Manfred Eigen, Philip Anderson, Stephen Jay Gould and
John Maynard Smith, etc.

CONTENTS

Themes

1. Conceptual Outline of Current Evolutionary Theory
The Emergence of the Neo-Darwinian Synthesis
Enlarging the Framework
Summary

Part I	Adaptation to the Edge of Chaos

2. The Structure of Rugged Fitness Landscapes
Fitness Landscapes in Sequence Space
The NK Model of Rugged Fitness Landscapes
Summary

3. Biological Implications of Rugged Fitness Landscapes

Phylogenetic Implication of Rugged Landscapes
Population Flow on Rugged Fitness Landscapes
Summary

4. The Structure of Adaptive Landscapes Underlying

Protein Evolution
Evolution of Novel Catalytic Functions
Applied Molecular Evolution: Direct Exploration
of DNA, RNA, and Protein Sequence Spaces
Summary

5. Self-Organization and Adaptation in Complex Systems

Dynamical Systems and Their Attractors
Spontaneous Order and Chaos in Complex Dynamic Systems
Summary

6. The Dynamics of Coevolving Systems

Coevolution in Ecosystems
Structured Ecosystems and Self-Organized Criticality:
Coevolution to the Edge of Chaos
Coevolutianary Conclusions
Summary

Part II  The Crystallization of Life

7. The Origins of Life: A New View

Background to the Origin of Life Problem
Autocatalytic Sets of Catalytic Polymers
Growth on the Infinite Graph of Polymers and
Thermodynamic Behaviour
Evolutionary Capacities of Autocatalytic Sets Without
a Genome
Experimental Consequences
Summary

8. The Origin of Connected Metabolism

Crystallization of a Connected Metabolism as a
Percolation Problem
New Experiments
Summary

9. Hypercycles and Coding

The Logic of Hypercycles
Bedian's Paradigm for the Onset of Coding
Summary

10. Random Grammars: Models of Functional Integration
and Transformation

Jets and Autocatalytic Sets: Towards a new String Theory
Infinite Boolean Networks and Random Grammars: Approaches
of Studying Families of Mappings of Strings into Strings
Application to Biological, Neural and Economic Systems
Summary

Part III  Order and Ontogeny

11. The Architecture of Genetic Regulatory Circuits and Its
Evolution

Independence of the Molecular Evolutionary Clock and
Morphological Evolution
Components in the Genetic Regulatory System of Prokaryontes
and Eukaryontes
An Ensemble Theory Basend on Random Directed Graphs
Summary

12. Differentiation: The Dynamical Behaviours of Genetic
Regulatory Networks

Simple Genetic Circuits and the Boolean Idealization
Large-Scale Features of Cell Differentiation
The Conceptual Framework: Cell Differentiation in
Boolean Networks
Ensembles of Genetic Regulatory Systems: Generic Properties
Implications for Ontogeny
Cell Types as a Combinatorial Epigenetic Code
Summary

13. Selection for Cell Types

The Framework
Genomic Network Space
Experimental Avenues
Summary

14. Morphology, Maps, and the Spatial Ordering of Integrated
Tissues

Induction as a Basic Intercellar Conversation
Evidence for a Long-Range Order in Tissues: Duplication,
Regeneration and Positional Continuity
The Spontaneous Generation of Spatial Patterns: Turing Models
Compartmental and Segmental Patterns in Drosophila melanogaster
Pattern Formation in the Early Drosophila Embryo
Spatial Harmonics Suggested by Mutants Affecting Segmentation:
Longitudinal Deletions and Mirror-symmetic Duplications
Sinuisoidal Transcription and Protein Patterns: A Bifurcation
Sequence of Higher Harmonics on the Egg
The Four Color Wheels Model of Positional Specification
Turing and Beyond
Summary

Epilogue

Bibliography

Index

P.S. "Read this book" says Philip Anderson from Princeton and I am
inclined to agree. It might not change the fundamentals of your
world view but it does certainly provide very valuable insights
on a variety of seemingly unrelated problems.
_________________________________________________________________________

"Anon rushed by the bright Hyperion;
His flaming robes streamed out beyond his heels,
And gave a roar, as if of earthly fire,
That scared away the meek ethereal Hours,
And made their dove-wings tremble. On he flared..." -- John Keats
_________________________________________________________________________

John R. Koza, "Genetic Programming -- on the programming of
computers by means of natural selection" (there is also the
successor volume "Genetic Programming II: Automatic Discovery of
Reusable Programs", which is also very good), 819 pp., MIT Press
(1992). (Btw MIT Press, I wonder how these dudes do it. You can
bloody buy any book they publish a priori, they are all so
phenomenally good).

This (also quite dusty) book is primarily interesting since it
gives many real-world examples of what digital evolution can do,
one is given an opportunity to aquire a feel of both what is
(was!) currently possible and the impact of different parameters
upon optimization kinetics without the need of being an expert
in the field; a rich conserve of second-hand experience. The
successor volume also steps in these tracks.

Contents
Preface
Acknowledgements

1 Introduction and Overview
2 Pervasiveness of the Problem of Program Induction
3 Introduction to Genetic Algorithms
4 The Representation Problem for Genetic Algorithms
5 Overview of Genetic Programming
6 Detailed Description of Genetic Programming
7 Four Introductory Examples of Genetic Programming
8 Amount of Processing Required to Solve a Problem
9 Nonrandomness of Genetic Programming
10 Symbolic Regression -- Error-Driven Evolution
11 Control-- Cost-Driven Evolution
12 Evolution of Emergent Behaviour
13 Evolution of Subsumption
14 Entropy-Driven Evolution
16 Co-Evolution
_______________________________________________________________

(An engraved (linear A; bous strophadon), roughly cylindrical
iridium artefact of unknown orgin recently discovered 10 m below
the surface in eternal methane snows of Mare Borges, Charon.
Isotope dating gave negative age).

"Non serviam" -- Lucifer.

Nondum -- hora ruit.

De profundis -- ad astra -- in aeternum.

Mente captus. Default at birth. Mostly incurable.

Mors porta vitae. Tell me another one.

{{Dewar porta vitae?}}

dv/dt -> \infty. Incipit.

Thanathos anathema sit.

Memento moriendum esse. Sooo sure?

In dubio pro >H.

"Non serviam" -- me.

"Natura non facit saltus" -- Carl von Linne.
"Bullshit" -- God.

"De nihilo nihil" -- Lucretius.
"Oh yeah?" -- God.

"Lasciate ogni speranza vo ch' entrai" -- gold inlay inscription
on porta dell'inferno.

"Arbeit Macht Frei" -- The Management. (massive black iron
lettering as seen from the other side).

Randy, you scroowed it all over, again. Bad boy.

Ecce >Homo!

"Specimen of early homo sapiens, now transiently defunct due to
ongoing restauration" -- label upon a fully interactive uploader
simulacrum installation in a museum futurum in Kuiper cloud.

"Cogito, ergo sum" -- deus ex machina, v.0.0.1.alpha during early boot phase
{{ previously erroneusly attributed to HAL }}

Only a dead conservativist is a good conservativist. Let's track them down.

Habemus >Hominem.

In principio erat Erratum. Let's fix things proper.

Singularity ad portas, hic et nunc.

Dies irae: "Consumatum est. Ceterum censeo..."

Credo, quia (non) absurdum.

E pluralis >H unum.

Gutta cavat lapidem. Come on, guys. Have a go at it.

Fiat lux. A nuke, anybody?

{{-- RollsRoyce supernova. Sorry, couldn't resist :}}

Eritis sicut deus, scientes bonum et malum.

You can't escape escapism.

"Ignorabimus" -- an anonymous loser. Deceased.

Hic Rhodus, hic salta. {{Hah, hah -- very funny. Who was the
wise guy with the superglue?}}

Deus, ipso facto.

Omega magnificat.

Licet.

Finis coronat opus.

Narrata refero.

"Firmware update on demand. Wetware recycling container to your
right at exit. Thanks for visiting us." -- Omega, Unltd.

Errare humanum est. Ergo...
{{it takes a >H to fabricate truly monumental shitpiles. Let's

>Homo homini lupus. What else?

"It is not alive, Jim, at least not alife as we know it"

Singularity ex abrupto. Nihil obstat.

"Duck -- and cooover!" -- Atomic Cafe

"Always proceed with the utmost subtility" -- Attila the Hun

"Would you care for a drink?" -- Catharina de Medici

"Ethics? Now just let me look it up..." -- Machiavelli

"Holy shit!" -- Edward Teller

Somebody better go tell Lucifer about all the brownouts.

Sysiphos is Prometheus in disguise.

No, there is no Omega conspiracy. Who are you and why do you

Scotty, beam me up. No intelligent life forms down here.

The world is like a jigsaw puzzle box: hard to begin, easy, once
pieces start fitting.

Run out of grand challenges, Real Hackers are yearning to hack
the Universe.

"The world will turn strange, soon"

"A global search of idea space is left as an exercise to the
user. Return universe in good shape for recycling. Thank you."
-- God.
______________________________________________________________

Christof Koch and Idan Segev (ed.), "Methods in Neuronal
Modeling -- From Synapses to Networks", MIT Press (1989, 1990),

_Very_ dusty -- and a heavy dampener for the too-bright-eyed
there is a congruency at the statespace kinetics level, so no
need to model every ion channel in the universe. "Singularity
aloha!" -- "You're quite in a (solid) state today, my dear").

Contents
Preface
1 Introduction
2 Cable Theory for Dendritic Neurons
3 Compartmental Models of Complex Neurons
4 Multiple Channels and Calcium Dynamics
5 Analysis of Neural Excitability and Oscillations
6 Reconstruction of Small Neural Networks
7 Associative Network Models for Central Pattern Generators
8 Spatial and Temporal Processing in Central Auditory Networks
9 The Simulation of Large-Scale Networks
10 Modeling the Mammalian Visual System
11 Simplifying Network Models of Binocular Rivalry and
12 Simulating Neurons and Networks Parallel Computers
13 Numerical Methods for Neuroal Modeling
_____________________________________________________________________
Valentin Braitenberg, "Vehicles. Experiments in Synthetic Psychology",
MIT Press (1984), 147 pp (Kraut version).

Dusty beyond belief and very shallow. Nevertheless readable (at
least after the second sixpack..).

Contents (from Krautspeak, so don't hit me)

Being  1: Roaming
Being  2: Timidity and Agression
Being  3: Love
Being  4: Values and Taste
Being  5: Logic
Being  6: Selection, the Faceless Engineer
Being  7: Concepts
Being  8: Space, Things, Movement
Being  9: Gestalt
Being 11: Having Ideas
Being 12: Laws and Recurrencies
Being 13: Catenating Thoughts
Being 14: Prediction
Being 15: Egoism and Optimism
__________________________________________________________________

Gregoire Nicolis, Ilya Prigogine (ed.), "The Exploration of the
Complex -- on the Way of a New Understanding of Natural
Sciences", (1987). (or somesuch since it is in Kraut, again. Is
purported to have been translated from Yanglish, no OCM
(original crap manufacturer) source is given, however).

A very readable collection of interdisciplinary
introductory-level complexity science papers.

Dust? Which dust?
____________________________________________________________________

"There was a young man called Kleene
Who invented a fucking machine
Concave or convex --
it fit either sex
and was exceedingly easy to clean".

-- limerick, attributed to John von Neumann
____________________________________________________________________

K. Eric Drexler, "Nanosystems. Molecular Machinery,
Manufacturing, and Computation", Wiley-Interscience (1992), 556 pp.

(Quite useless to mention it here, obviously, just for the
completeness sake). Is not Scripture, of course, but gives a
goodly number of extremely valuable suggestions and insights.
Quite succinctly put: Read This Book.

No Contents given, since you can find them on the web. Foresight
will probably put the whole hog online quite soon as it recently
did with "The Engines of Creation" (topsy-turvy priority, imo),
though they royally botched it up by not having had TeXed it
right from the start latex2html((La)TeX+PostScript)-->HTML.
Trivial, in the retrospective. Foresight of "Foresight"? Well.)
____________________________________________________________________

Frank J. Tipler, "The Physics of Immortality", Doubleday New
York (1994), 605 pp. (Kraut, again). (Too lazy to give Contents
since it's quite formidable, so there. Translating sucks right
royally, no?).

Brilliant physics and cosmogony, lots of >H philosophy, far too
much trashy cult comparativistics. Definitely a >H literature.
_____________________________________________________________________

Daniel P. Sieworek and Robert S. Swarz, "Reliable Computer
Systems -- Design and Evaluation" (it also features an in-depth
discussion concerning instrumental difficulties of taming wild
black unicorns in Zanzibar and politically correct dealings with
the Bendith Y Mamau (only distantly related to Daoine Sidhe)),
Digital Press (1992), 908 pp.

Mostly examples of how one can spend the rest of one's life by
nursing old injuries from iterative shooting in one's both feet,
quite a long time ago -- and earning quite serious money in the
process. Also grazes in fly-by spacecraft probe reliability
design, which is otherwise not easy to come by.
_____________________________________________________________________

Alan Murray and Lionel Tarassenko, "Analogue Neural VLSI - a
Pulse Stream Approach", Chapman & Hall (1994), 147 pp.

I am far from being through yet -- but it is roughly what Carver
Meade (of silicon retina fame) does, albeit on the right side of
the Atlantic. I don't think Si 2d photolitho is the ticket, it
is interesting how far one can progress with this inherently
limited technology, however.

Contents
Preface

1 Why building neural networks in analogue VLSI?
1.1 Introduction
1.2 Hopfield memories -- the first generation of neural
network VLSI
1.3 Pattern classification using neural networks
1.3.1 Single-layer networks
1.3.2 Multi-layer networks
1.3.3 Conclusion
1.4 Why build neural networks in silicon?
1.5 Computational requirement
1.5.1 Digital or analogue?

2 Neural VLSI - A review
2.1 Introduction
2.2 MOSFET equations - a crash course
2.3 Digital accelerators
2.4 Op-amps and resistors - a final look
2.5 Subthreshold circuits for neural networks
2.6 Analogue/digital combinations
2.7 MOS transconductance multiplier
2.8 MOSFET analogue multiplier
2.9 Imprecise low-area "multiplier"
2.10 Analogue, programmable - Intelectronically-Trainable
Artificial Neural Network (ETANN) chip
2.11 Conclusion

3 Analogue synaptic weight storage
3.1 Introduction
3.2 Dynamic weight storage
3.3 MNOS (Metal Nitride Oxide Silicon) networks
3.4 Floating-gate technology
3.5 Amorphous Silicon (alpha-Si) synapses
3.5.1 Forming at higher temperatures
3.5.2 Deposition of metal during alpha-Si growth
3.5.3 Investigation of the forming process
3.5.4 Programming technology

4 The pulse stream technique
4.1 Introduction
4.2 Pulse encoding of information
4.2.1 Pulse amplitude modulation
4.2.2 Puse width modulation
4.2.3 Pulse frequency modulation
4.2.4 Phase or delay modulation
4.2.5 Noise, robustness, accuracy and speed
4.3 Pulse stream technique -- addition and multiplication
4.3.1 Addition of pulse stream signals
4.3.2 Multiplication of pulse stream signals
4.4 Pulse stream communication
4.4.1 Asynchronous intercommunication using pulse time
information
4.5 Conclusions

5 Pulse stream case studies
5.1. Overall introduction to case studies
5.1.1 Introduction -- Edinburgh
5.2 The EPSILON (Edinburgh Pulse-Stream Implementation of
a Learning-Oriented Network) chip
5.3 Process invariant summation and multiplication -- the
synapse
5.3.1 The transconductance multiplier
5.3.2 A synapse based on distributed feedback
5.3.3 The feedback operational amplifier
5.3.4 A voltage integrator
5.3.5 The complete system

5.4 Pulse frequency modulation neuron
5.4.1 A pules stream neuron with electrically adjustable
gain
5.5 Pulse width modulation neuron
5.6 Switched-capacitor design
5.6.1 Weight linearity
5.6.2 Weight storage time
5.6.3 Accuracy of computation
5.7 Per-pulse computation
5.7.1 Design overview
5.7.2 Input stage
5.7.3 Synapse
5.7.4 Summation neuron
5.7.5 Sigmoid function
5.7.6 Pulse regeneration
5.7.7 SPICE simulation
5.7.8 Results from test chips
5.7.9 Synapse linearity
5.7.10 Input sample and hold
5.7.11 Sigmoid transfer function
5.7.12 Output pulse stream generation
5.7.13 Weight precision
5.7.14 Weight update
5.7.15 Per-pulse Computation Summary
5.8 EPSILON - The chosen neuron/synapse cells, and results
5.8.1 The EPSILON design
5.8.2 Synapse
5.8.3 Neurons
5.8.4 EPSILON specification
5.8.5 Application - vowel classification
5.9 Conclusion

6. Application examples
6.1 Introduction
6.2 Real-time speech recognition
6.3 Application of neural VLSI
6.4 Application of neural VLSI - dedicated systems
6.4.1 Path planning
6.4.2 Localization
6.4.3 Obstacle detection/avoidance
6.4.4 Conclusion
6.5 Application of neural VLSI -- hardware coprocessors
6.6 Application of neural VLIS -- embedded neural systems
6.7 Conclusion

7. The future
7.1 Introduction
7.2 Hardware learning with multi-layer perceptrons
7.3 The top-down approach: Virtual Targets
7.3.1 "Virtual Targets" Method -- In an I:J:K MLP network
7.3.2 Experimental results
7.3.3 Implementation
7.4 The bottom-up approach: weight perturbation
7.5 Test problems
7.7 Back-propagation revisited (for the final time?)
7.8 Conclusion
7.9 Noisy synaptic arithmetics -- an analysis
7.9.1 Mathematical predictions
7.9.2 Simulations
7.9.3 Prediction/verification
7.9.4 Generalization ability
7.9.5 Learning trajectory
7.10 Noise in training -- some conclusions
7.11 On-chip learning -- conclusion

References
Index
(whew! lots of incredible contents for just 147 pages).
________________________________________________________________

itchy-bitchy tiny-wienie.. erm. skip that.

"Mayest thou live in interesting times" -- old Chinese curse

"The West is the Best" -- The Doors

"The West is the Best" -- Randall Flagg
________________________________________________________________

Melanie Mitchell, "An Introduction to Genetic Algorithms", MIT
Press (1996), 205 pp.

Done by the incredible Melanie Mitchell, the high priestess of
the Santa Fe complexity shrine. (Sometimes I wonder whether
Santa Fe Institute's location has something to do with the
soaring-high quality of research done there... probably downwind
of the Livermore Labs?). If only they would put more of their
stuff online...

Looked for dust, found none. It seems GA gurus start stealing
from nature in earnest now. Good. Singularity is beckoning.

Contents

Preface
Acknowledgements

1. Genetic Algorithms: An Overview

A Brief History of Evolutionary Optimization
The Appeal of Evolution
Biological Terminology
Search Spaces and Fitness Landscapes
Elements of Genetic Algorithms
A Simple Genetic Algorithm
Genetic Algorithms and Traditional Search Methods
Some Applications of Genetic Algorithms
Two Brief Examples
How Do Genetic Algorithms Work?
Thought Exercises
Computer Exercises

2 Genetic Algorithms in Problem Solving

Evolving Computer Programs
Data Analysis and Prediction
Evolving Neural Networks
Thought Exercises
Computer Exercises

3 Genetic Algorithms in Scientific Models

Modeling Interactions Between Learning and Evolution
Modeling Sexual Selection
Modeling Ecosystems
Measuring Evolutionary Activity
Thought Exercises
Computer Excercises

4 Theoretical Foundations of Genetic Algorithms

Schemas and Two-Armed Bandit Problem
Exact Mathematical Model of Simple Genetic Algorithms
Statistical-Mechanics Approaches
Thought Exercises
Computer Exercises

5 Implementing a Genetic Algorithm

When Should a Genetic Algorithm Be Used?
Encoding a Problem for a Genetic Algorithm
Slection Methods
Genetic Operators
Parameters for Genetic Algorithms
Thought Exercises
Computer Exercises

6 Conclusion and Future Directions

Appendix A Selected General References
Appendix B Other Resources
Bibliography
Index
__________________________________________________________________

Christopher G. Langton (ed.), "Artificial Life -- An Overview",
MIT Press (1995), 340 pp. Negligeable layer of dust.

A sampler from the first three issues of "Artificial Life". Very
cheap, very delicatessen. Has lots of high-quality references in
it -- probably the best way to bootstrap you into the exciting
field of ALife. I am going to bring some quotes in the next post
because some of them are so sparkly.

Contents
Editor's Introduction

Artificial Life as a Tool for Biological Inquiry

keywords -- artifical life, evolution, natural selection, origin
of life, development, wetware, emergent properties

abstract -- Artifical life embraces those human-made systems
that posess some of the key properties of natural life. We are
specifically interested in artifical systems for the
investigation of open questions in biology. First we review some
of the artificial life models that have been constructed with
biological problems in mind, and classify them by the medium
(hardware, software, or "wetware") and by level of organization
(molecular, cellular, organismal, or population). We then
describe several "grand challenge" open problems in biology that
seem especially good candidates to benefit from artificial life
studies, including the origin of life and self-organization,
cultural evolution, origin and maintanance of sex, shifting
balance in evolution, the relation between fitness and
adaptedness, the structure of ecosystems, and the nature of
mind.

Cooperation and Community Structure in Artificial Ecosystems

keywords -- evolution, Prisonner's Dilemma, cooperation,
communitiy structure, food webs, lattice games

abstract -- We review results on the evolution of cooperation
based on the iterated Prisonner's Dilemma. Coevolution of
strategies is discussed both in situations where everyone plays
against everyone, and for spatial games. Simple artificial
ecologies are constructed by incorporated an explicit resource
flow and predatory interactions into models of coevolving
strategies. Properties of food webs are reviewed, and we discuss
what artifical ecologies can teach us about community structure.

Extended Molecular Evolutionary Biology: Artificial Life
Bridging the Gap Between Chemistry and Biology

keywords -- evolutionary biotechnology, molecular evolution,
quasi-species, RNA replication, RNA structure, shape space,
template chemistry

abstract -- Molecular evolution provides an ample field for the
extension of Nature's principles towards novel applications.
Several examples are discussed here, among them are evolution in
the test tube, nucleotide chemistry with new base pairs and new
backbones, enzyme-free replication of polynucleotides and
template chemistry aiming at replicating structures that have
nothing in common with the molecules from nature.
Molecular evolution in the test tube provides a uniquely simple
system for the study of evolutionary phenomena: genotype and
phenotype are two features of one and the same RNA molecule.
Then fitness landscapes are nothing more than combined mappings
from sequences to structures and from structures to functions,
the latter being expressed in terms of rate constants. RNA
phenomena in reality by mathematical analysis and computer
simulation is feasible. New questions concerning stability of
structures in evolution can be raised and quantitative answers
are given.
Evolutionary biochemistry is a spin-off from molecular
evolution. Darwin's principle of variation and selection is
applied to design level biopolymers with predetermined
functions. Different approaches to achieve this goal are
discussed and a survey of the current state of the art is given.

Visual Models of Morphogenesis

keywords -- morphogenesis, simulation and visualization of
biological phenomena, developmental model, reaction-diffusion,
diffusion-limited growth, cellular automaton, L-system,
realistic image synthesis

abstract -- Rapid progress in the modeling of biological
structures and simulation of their development has occured over
the last few years. It has been coupled with the visualization
of simulation results, which has led to a better understanding
of morphogenesis and given rise to new procedural techniques for
realistic images synthesis. This paper reviews selected models
of morphogenesis with a significant visual component.

The Artificial Life Roots of Artificial Intelligence

keywords -- autonomous robots, artificial intelligence, adaptive
behaviour

abstract -- Behaviour-oriented Artificial Intelligence (AI) is a
scientific discipline that studies how behaviour of agents
emerges and becomes intelligent and adaptive. Success of the
field is defined in terms of success in building physical agents
that are capable of maximizing their own self-preservation in
interaction with a dynamically changing environment. The paper
addresses this Artificial Life route toward AI and reviews some
of the results obtained so far.

Towards Synthesizing Artificial Neural Networks that Exhibit
Cooperative Behaviour: Some Open Issues in Artifical Life

keywords -- artifical neural networks, evolution of
communication, evolution of predation, cooperative behaviour,
genetic algorithm

abstract -- The tasks that animals perform require a high degree
of intelligence. Animals forage for food, migrate, navigate,
court mates, rear offspring, defend against predators, construct
nests, and so on. These tasks commonly require social
interaction/cooperation and are accomplished by animal neural
systems, which are the result of billions of years of evolutino
and complex environmental/learning processes. The Artificial
Life (AL) approach to synthesizing intelligent behaviour is
examine soem of the numerous open problems in synthesizing
intelligent animals behaviour (especially cooperative behaviour
involving communication) that face the field of AL, a discipline
still in its infancy.

keyboards -- autonomous agents, behaviour-based artificial
intelligence, artificial creatures, action selection, learning
from experience

abstract -- One category of research in Artificial Life is
concerned with modeling and building so-called adaptive
autonomous agents, which are systems that inhabit a dynamic,
unpredictable environment in which they try to satisfy a set of
time-independent goals or motivations. Agents are said to be
adaptive if they improve their competence at dealing with these
goals based on experience. Autonomous agents constitute a new
approach to the study of Artificial Intelligence (AI), which is
highly inspired by biology, in particular ethology, the study of
animal behaviour. Research in autonomous agents has brought
about a new wave of excitement into the field of AI. This paper
reflects on the state of the art of this new approach. It
attempts to extract its main ideas, evaluates what contributions
have been made so far, and identifies its current limitations
and open problems.

Chaos as a Source of Complexity and Diversity of Evolution

keywords -- chaos, evolution, edge of chaos, clustering, coupled
map, homeochaos, differentiation, complexity, genetic algorithm

abstract -- The relevance of chaos to evolution is discussed in
the context of the origin and maintanance of diversity and
complexity. Evolution to the edge of chaos is demonstrated in an
imitation game. A an origin in diversity, dynamic clustering of
identical chaotic elements, globally coupled each to each other,
is briefly reviewed. The clustering is extended to nonlinear
dynamics on hyperbolic lattices, which enables us to construct a
self-organizing genetic algorithm. A mechanism of maintanance of
diversity, "homeochaos", is given in an ecological system with
interaction among many species. Homeochaos provides a dynamic
stability sustained by high-dimensional weak chaos. A novel
mechanism of cell differentiation is presented, based on dynamic
clustering. Here, a new concept -- "open chaos" -- is proposed
for the instability in a dynamical system with growing degrees
of freedom. It is suggested that studies based on interacting
chaotic elements can replace both top-down and bottom-up
approaches.

An Evolutionary Approach to Synthetic Biology: Zen and the
Art of Creating Life

keywords -- evolution, ecology, synthesis, parallel computation,
multi-cellularity, complexity, diversity

abstract -- Our concepts of biology, evolution and complexity
are constrained by having observed only a single instance of
life, life on earth. A truly comparative bilogy is needed to
extend these concepts. Because we cannot observe life on other
planets, we are left with the alternative of creating Artificial
Life forms on earth. I will discuss the approach of inoculating
evolution by natural selection into the medium of the digital
computer. This is not a physical/chemical medium; it is a
logical/informational medium. Thus, these new instances of
evolution are not subject to the same physical laws as organic
evolution (e.g. the laws of thermodynamics) and exist in what
amounts to another universe, governed by the "physical laws" of
the logic of the computer. This excercise gives us a broader
perspective on what evolution is and what it does.

An evolutionary approach to synthetic biology consists of
inoculating the process of evolution by natural selection into
an artificial medium. Evolution is then allowed to find the
natural forms of living organisms in the artificial medium.
These are not models of life, but independant instances of life.
This essay is intended to communicate a way of thinking about
synthetic biology that leads to a particular approach: to
understand and respect the natural form of the artificial
medium, to facilitate the process of evolution in generating
forms that are adapted to the medium, and to let evolution find
forms and processes that naturally exploit the possibilities
inherent to the medium. Examples are cited of synthetic biology
embedded in the computational medium, where in addition to being
an exercise in experimental comparative evolutionary biology, it
is also a possible means of harnessing the evolutionary process
for the production of complex computer software.

Beyond Digital Naturalism

keywords -- organization, self-maintanace, lambda-calculus,
evolution, hierarchy

abstract -- The success of Artificial Life (Alife) depends on
whether it will help solve the conceptual problems of biology.
Biology may be viewed as the science of the transformation of
the organizations. Yet biology lacks a theory of organization.
We use this as an example of the challenge that ALife must meet.

keywords -- decentralized systems, emergence, education,
simulations, centralized mindsett, epistemology

abstract -- The growing interest in Artificial Life is part of a
broader intellectual movement towards decentralized models and
metaphors. But even as decentralized ideas spread through the
culture, there is a deep-seated resistance to these ideas.
People have strong attachements to centralized control where
none exists. New types of computational tools and construction
kits are needed to help people move beyond this "centralized
mindset". Perhaps most important are new tools and activities
for children, to help them develop new ways of looking at the
world.

Books on Artifical Life and Related Topics (no abstracts)

Computer Viruses as Artifical Life

keywords -- artificial life, ethics, computer virus

abstract -- There has been considerable interest in computer
viruses since they first appeared in 1981, and especially in the
past few years as they have reached epidemic numbers in many
personal computer environments. Viruses have been written about
as a security problem, as a social problem, and a possible means
of performing useful tasks in a distributed computer
environment. However, only recently have some scientists begun
to ask if computer viruses are not a form of artificial life --
a self-replicating organism. Simply because computer viruses do
not exist as organic molecules may not be sufficient reason to
dismiss the classification of this form of "vandalware" as a
form of life. This paper begins with a description of how
computer viruses operate and their history, and of the various
ways computer viruses are structured. It then examines how
viruses meet properties assotiated with life as defined by some
researchers in the area of artificial life and self-organizing
systems. The paper concludes with some comments directed towards
the definition of artificially alive systems and experimetation.

Genetic Algorithms and Artificial Life

abstract -- Genetic algorithms are computational models of
evolution that play a central role in many artificial-life
models. We review the history and current scope of research on
genetic algorithms in artificial life, giving illustrative
examples in which the genetic algorithm is used to study how
learning and evolution interact, and to model ecosystems, immune
system, cognitive systems, and social systems. We also outline a
number of open questions and future directions for genetic
algorithms in artificial-life research.

Artificial Life as Philosphy (no abstracts)

Levels of Functional Equivalence in Reverse Bioengineering

keywords -- computationalism, evolution, functionalism, reverse
engineering, robotics, symbol grounding, synthetic life, virtual
life, Turing test

abstract -- Both Artifical Life and Artificial Minds are
branches of what Dennet has called "reverse engineering":
Ordinary engineering attempts to build systems to meet certain
functional specifications; reverse bioengineering attempts to
understand how systems that have already been built by the Blind
Watchmaker work. Computational modeling (virtual life) can
capture the formal principles for life, perhaps predict and
explain it completely, but it can no more to _be_ alive than a
virtual forest fire can be hot. In itself, a computational model
is just an ungrounded system; no matter how closely it matches
the properties of what is being modeled, it matches them only
formally, with the mediation of an interpretation. Synthetic
life is not open to this objectionn, but it is still an open
question how close a functional equivalence is needed in order
to capture life. Close enough to fool the Blind Watchmaker is
probably close enough, but would that require molecular
indistinguishability, and if so, do we really need to go that
far?

{{weak, very weak. So an expert system just fakes solutions to
problems, Deep Though did not really beat Kasparov, only in some
transcendent, unreal sense? Sure enough nobody ever gets
flashfried by Livermore Lab simulation runs. Any uploader
volunteers?}}

Why Do We Need Artifical Life?

keywords -- AL and Art, AL and theoretical bilogy, AL and
engineering, AL and You, boundary conditions, epistemology,
levels of analogy, reductionism, synthesis

abstract -- In this paper we ask the question of whether we need
artificial life (AL) at all. We find a lot of convincing
arguments in favor of AL, but we also point out some dangers AL
is exposed to. This careful epistemological review reveals the
potential richness of AL without being too reductionist or too
holistic. We give some examples showing how this can be done in
practice, and conclude that almost everybody needs AL.

Index

__________________________________________________________________

Now I feel quite distinctly dead//and my keyboard is splattered
red//should I've done something better with my time, instead?

'gene

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