self-organised reality brian josephson department of physics university of cambridge

Self-organised Reality

Brian Josephson

Department of Physics

University of Cambridge

Utrecht II, Oct. 17, 2008 Self-organised reality/Brian Josephson 2

Main theme

• Classical picture: fixed fundamental law

• This alternative: emergent laws

• Need to think in very different ways to the usual!


Sources

• Maturana and Varela (autopoiesis)

• Steve Rosen (emergent order, phenomenology)

• Stu Kauffman (self-organisation and life)

• Ilexa Yardley (circular theory)


Main themes

• Edge of chaos, order-disorder balance

• Life as intermediate level of order: chance, necessity and intelligence

• Cycles, attractors, ambiguity

• Mutual support, observation

• Circular thought, ‘post-explanatory reasoning’


Edge of chaos

• Deterministic chaos: sensitive dependence on initial conditions, effective unpredictability

• ‘Edge of chaos’: boundary between order and chaos

• Rapid evolution


Order-disorder interplay

• Order creates order out of disorder

(through ‘intelligent’ observation)

• Disorder introduces noise into order

• Systems form and disintegrate


Life itself

• Between order and disorder

• Too much order, not alive

• Too much disorder, not alive

• Life shapes itself (autopoiesis)

• Confines itself to a limited range of possibilities


Restricted range

• Range must be enough to be able to embody resources needed to be able to shape itself under all conditions

• Must act in a precise way, hence requirement for restriction

• Analogy: computer programs


Cycles

• Cycles are a universal phenomenon associated with restricted range

• Too simple to be considered life, but perhaps essential component of life


Subsystems and models

• Biosystems contain subsystems whose behaviour can be related to models

• Models show how parts work together

• With complex systems, all models are limited; there is always something outside a given model, possibly ‘intelligent’


Chance, Necessity and Intelligence

• By chance, parts that can work together come together

• Working together is a necessity for continued existence of the collection

• The fact of continued existence can be deemed a manifestation of intelligence; thus intelligence naturally exists


Observation and information

• Effective action is the effective use of information based on observation

• Triadic mechanism: one system coordinates the behaviour of two others (example: actions involved in walking)


Significant interrelations

• These processes lead to systems becoming related to each other in a significant way

• Accumulation of parts leads to complex biosystems

• 1, 2, 3, many; emergent communities


Dynamic systems perspective

• Model system as point in many-dimensional space

• Rigid system, minimal motion• Chaotic system, roaming widely• Intermediate case: roaming in a restricted region

(e.g. simple or extended cycle, attractor situation)• Forming and disintegrating


Evolution/development

• Roaming limited by homeostatic shaping mechanisms

• Evolution/development from alternating conservative and active phases


Conservative and active interplay

• End up with organisations most resistant to destabilisation: destabilisation in the interests of stability


Joy of Approximation I

• System does not have to fit a specific model to be able to be functional (nature uses empirical approach)

• Advance via approximations

• Evolution finds good, combinable approximations

• Problematic for scientists!


Joy of Approximation II

• A subsystem works ‘roughly like model X’

• Then something happens and it starts working roughly like modification Xso it goes on

• Life uses approximations but is not bound by them (open system)


Observation

• Observation = key process: information processing with some meaningful outcome

• Develops to extract useful information

• Two systems can exchange information to assist in acting as one highly integrated system for specified tasks (assisted by 3rd member of a triad?)


Achievement and potentiality

• Life continues till something works, what does not work gets discarded

• Chance observation of what works in a given context leads to progress

• Reality involves a field of potentiality, things that worked in some context in the past

• Emergence cannot be captured in a formula


Potentiality and meaning

• The meaning of something is what may come of it, its potential

• Intelligent observer systems can take account of potentiality, thus connecting the real with the unreal


History, known and ‘dark’

• The past affects present probabilities, in ways we cannot know in detail

• ‘Dark’ history; intelligent design?


Objective reality

• [speculative] According to C S Peirce, ‘thirdness’, involving knowledge of the relationships between things, is the basis of objective reality

• Hence(?) a group of 3 observers can create something objective, which can be taken up by others


Objective Space

• By extension, something with the characteristics of a space of a particular kind can be created by a group of observers acting in coordination with each other

• cf. flocking of birds


What is this all about, anyway?

• Ideas have been extracted from both biology, and physics (order-disorder component) to get something that may be more general

• By making unclarity an integral part of science we may be getting closer to the truth


Application

• We have abducted principles from biology in order to apply them elsewhere (fundamental physics)

• Characteristic quantum properties such as wholeness, indeterminism, the role of the observer in deciding between alternatives, come out naturally within this approach


Application to psi

• Intelligent observation systems can take account of meaning and potentiality

• They discover meaningful possibilities, and develop relationships with them so as to help realise them (cf. Schoenberg on musical creativity)

• Space is a constructed phenomenon and action is possible outside it, so not limited by space (observers can be outside space-time)


Application in conventional physics

• Something to do for string theorists out of a job (?)


THE END

self-organised reality brian josephson department of physics university of cambridge

Documents

intelligent slide

walking slide

order systems

orderdisorder balance

chaos rapid evolution

intermediate level of

models models

intelligence cycles