Bogatyreva O.A, Bogatyrev N.R. Complexity in living and non-living systems
/ Proc. Of international TRIZ conference, Philadelphia, USA, 16-18 March 2003, p. 16/1- 16/6 .
COMPLEXITY IN LIVING AND NON-LIVING SYSTEMS
Olga Bogatyreva, Nickolaj Bogatyrev
The Centre for Biomimetics and Natural Technologies, Department of
Mechanical Engineering, the University of Bath, BA2 7AY, ensob@bath.ac.uk,
ABSTRACT
TRIZ deals with systems, most of which possess a high level of complexity. However
the very idea of complexity is not well realised nor properly comprehended in this theory.
Can living systems help technological industries better understand complexity and
emergent effects? Can we use biomimetics to achieve this aim? What sorts of relations
exist between complexity and reliability? These questions are discussed in our paper, as we
investigate structural and functional complexity in biology and technology.
I. INTRODUCTION
In spite of the fact that there are a vast number of publications on complexity theory,
applications to engineering are still obscure. In this paper we would like to find out answers
to the following questions:
1. Is there any difference between complexity in living and non-living systems?
2. If we define technology as ‘the combination of living and non-living parts’, what
then results in complexity for this combination?
3. What is the role of complexity and simplicity in system evolution (is it “good” or
“bad” for a system to be complex?)
4. Is progress always connected with increasing complexity?
All these questions look too theoretical, but there is one very essential point for
practical engineering: we need to know when a product is ready for simplification.
In the first stages of the evolution of a technological system, complexity increases,
and then in the later stages it decreases (1). This trend is observed in TRIZ and also by
Edward De Bono (2). However, neither TRIZ nor De Bono has any clear guidelines to
describe when, in the course of an S-curve, the shift from increasing to decreasing
complexity takes place. D. Mann (1) suggests that the shift takes place at a point of
maximum viable complexity – beyond which the problems that come with the increased
complexity outweigh the benefits (3). Yet he also does not look for evidence of any natural
equivalent of the trend.
In short, TRIZ has recognized the trend of complexity-followed-by-simplicity in
technology, but not in nature, although biologists and social ecologists (4) would say it is
quite well known. Humans, actually, are morphologically simplified apes…
So, the problem of shift is very practical. All theoretical questions we have asked in
this introduction can help us define some system characteristics that might show this
interesting shift point.
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Bogatyreva O.A, Bogatyrev N.R. Complexity in living and non-living systems
/ Proc. Of international TRIZ conference, Philadelphia, USA, 16-18 March 2003, p. 16/1- 16/6 .
2. COMPLEXITY IN LIVING AND NON-LIVING SYSTEMS
There are five general features in the scientific definition of complexity (4,5):
1. Complex systems have closely connected parts.
2. Knowing behaviour of parts does not enable us to predict system behaviour.
3. Dynamical behaviour might be classified into ‘order’, ‘complexity’, ‘chaos’, and
‘randomness’. All these parts are not mutually exclusive (4). Complexity is somewhere in
the middle between chaos and order. The phenomenon of life is typically complex. Nonliving systems are either in chaos or in order (5, 6, fig.1).
4. Complexity breaks symmetry (in a case of pre-existing order, it breaks ‘structural
symmetry’, in the case of pre-existing chaos, ‘probability symmetry’) (6, fig.1).
Fig. 1. Relative entropy of a system as an index of life definition
where H – entropy of the system, Hmax – maximum entropy of the system.
So, what is complexity? More or less, something that is difficult for us to understand
and predict as a whole, without decomposition into parts. It is something at a scale of space
and time that differs from our scale, and is thus difficult to imagine. For example, if it as
big as the Universe or small as a cell, it is difficult to describe, model and predict (fig.2 ).
Likewise, when technical systems act on a similar scale with us, they seem to be
simple, when they are bigger/too slow or smaller/too fast, they seem to be complex to
understand. We always want to simplify technology, but is there ever a real simplification
of it?
Let us take an example from D. Mann’s paper in TRIZ-journal (1) about a strip with
the ‘shape change with temperature’ function. First it was bi-metallic and there were three
or more components (the two different metals plus some intermediary agent to bond the
two together). Then the function of the bi-metallic strip was delegated to a ‘single’ shapememory alloy. But the overall ‘complexity’ of the system did not decrease. It has instead
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Bogatyreva O.A, Bogatyrev N.R. Complexity in living and non-living systems
/ Proc. Of international TRIZ conference, Philadelphia, USA, 16-18 March 2003, p. 16/1- 16/6 .
been subsumed into the sub-system structure of the constituent parts that is far from our “0”
on time/space scale (fig.2). In other words, although a shape-memory alloy replaces three
or two parts with one, it has largely done so through clever configuration of the crystal
structure of the alloy – and as such, the complexity has been transferred from the engineer
to the materials scientist (1).
Fig. 2. Complexity in man space/time scale.
It means that all technology simplification has sense only on that “point” of
time/space scale that we can comprehend. And all simplification in technology evolution is
nothing but delegating all complexity to sub-systems level. In other words, the ideal result
is something that works, but we cannot see how.
Fig. 3. Complexity and simplicity in living systems development.
Defining of shift points from complexity to simplicity.
LS – living systems, N/LS – non-living systems, T/S – technological system, IFR –
ideal final result
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Bogatyreva O.A, Bogatyrev N.R. Complexity in living and non-living systems
/ Proc. Of international TRIZ conference, Philadelphia, USA, 16-18 March 2003, p. 16/1- 16/6 .
Let us have a look at living systems. Do they develop towards complexity? Increasing
complexity in living systems is always connected with the necessity of saving its
wholeness. When a system is too complex to maintain itself, it comes to a shift point – to
simplify functioning of its elements or to die. Such functional simplification in biology is a
specialisation. We estimated these shift points by the index of relative entropy studying
evolution of societies in social insects, apes and humans (5, fig.3).
Trends of evolution and ideal final results of living, non-living and technical systems
are different (fig3). Life tends to grow and spread in space and time (IFR for LS), but this
is possible only with its functional simplification (specialisation), otherwise there will not
be enough resources on Earth. Ideal final result for non-living systems (IFR for N/LS) is
structural and functional simplification (entropy increasing), while technology evolves in
the opposite direction to life systems – ideal final result for any technical device is
structural simplification but functional complexity (fig.3).
So, technology, when it imitates living systems, comes to highly-specialised, complex
products. Paths of biological and technical evolution are different and biological evolution
is not suitable for imitation in technology if we need simple poly-functional (high
adaptable) products. But if technology has a goal of creating artificial life, or life-like
systems (sustainable and autonomous) (fig.1), it probably needs to change its ideal final
result and evolve towards a structural complexity combining with functional simplification
of its elements.
Apart from functional and structural complexity there is “organisational”
(algorithmic) complexity – complexity of interactions (connections) between sub-systems,
rules of system behaviour (table. 1).
Simple
Complex
Structure
(“hard-ware” of a
system)
Table 1. Complexity in “soft-ware” and “hard-ware” of a system
Examples
from
Biology
Rules, algorithm (“soft-ware” of a system)
Simple
Complex
Bacteria, Protozoa
Behavioural hierarchy
Technology
Thermometer
Flute
Biology
Blood system
Ecosystem
Technology
Cellular automata
Internet
3. COMPLEXITY AND RELIABILITY.
Complexity is often discussed in connection with system reliability or sustainability.
Both structurally complex and simple systems can be reliable or non-reliable. For example,
simple and reliable is hand hammer, but simple and non-reliable can be any disposal
product. Natural ecosystems are complex and reliable, but complex artificial ecosystems
are not reliable.
Reliability can be provided by system “hardware”:
 structural surplus (extra-strength of dams, bridges);
 functional surplus (multifunctional devices)
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Bogatyreva O.A, Bogatyrev N.R. Complexity in living and non-living systems
/ Proc. Of international TRIZ conference, Philadelphia, USA, 16-18 March 2003, p. 16/1- 16/6 .
and “software”:
 adaptability;
 integration.
Reliability can only be achieved if every element of a system performs several
functions and any function of a system is supported by several structures (7). But what does
it mean – “several”, how many is enough for system reliability?
System reliability can vary depending on particular parameters. For example, a
system can be very reliable in resistance to wear, but non-reliable in functioning…
Adaptability, on the other hand, should not damage integrity. The system is reliable when
it’s relative entropy index is in the “corridor” of distribution of integrity parameter of its
parts (fig. 2, 3). Artificial/technical systems do not need exact copying of natural
prototypes. The right strategy is to take the best features of living systems and to get rid of
the weakest sides of them. Advantages of non-living nature and living nature should be
combined. The shortcoming of biological systems is complexity, and the weakest link of
non-living systems is simple (primitive) functioning. Combinations of complex functioning
(poly- functionality senso lato) of living and structural simplicity of non-living systems
would provide the desirable character (ideal final result) of the future technologies.
CONCLUSIONS.
1.
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3.
4.
Complexity of any system is connected with their stochastic behaviour and selforganisation, the number of their parts and number of functional connections between
them. But complexity of living and mixed (living + non-living) technological systems
has some peculiarities.
Non-living systems display goal-directed behaviour, while living systems have goal
intended behaviour and free will. It makes them unpredictable and complex.
Technical systems are usually deterministic ones. In technical systems probability
cannot be the indicator of complexity (imagine a car engine that works with 80%
probability!)
Either in living nature or in technology, increasing complexity is connected with
simplification of its sub-system. Complexity and simplicity in the course of evolution
just changes their place in “System Operator”. Simplifying the system structure, we
increase sub-system complexity.
REFERENCES:
Mann D.L. Complexity Increases And Then… TRIZ Journal, 2002.
De Bono E., ‘Simplicity’, Viking, London, 1998.
Mann D.L. Hands-On Systematic Innovation, CREAX Press, April 2002.
Williams G.P. Chaos Theory Tamed. Joseph Henry Press, Washington, D.C., 1997
Bogatyreva O.A., Shillerov A.E. Social Synergetics. Novosibirsk, “Nauka”, 1998.
Pavard B., Dugdale J. An Introduction to Complexity in Social Science. GRICIRIT, Toulouse, France,2002.
7. Mollison B. Permaculture: a designer’s manual. Tyalgum. – Tagary Publications,
NSW 2484, Australia, 1998.
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