WWCS2015 presentation

Scale interaction

Viktoras, Marta

Complex systems andscales

Scales

Scalable systems

Scale interactions

Evolution of complexsystems

Simulation modeling

The project proposal

Computational model

Simulation environment

Simulation of a socialsystem

What’s new

References

Interaction of scales in a complex system:simulation modelling approach

Viktoras Veitas,Marta Lenartowicz

Project proposal for/at WWCS2015

January 25, 2015Brussels

Viktoras, Marta (WWCS2015) Scale interaction January 25, 2015 1 / 17

Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References

Complex systems and scales

Conjecture #1: complex systems are not beingdesigned - they self-organize [7];

Conjecture #2: complex systems are (self-)organizedin scales [8];


Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References

Illustration of scales

[8]


Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References

Examples of scalable systems

Ecological niches, social systems, biologicalorganisms, brain,

System S-1 S S+1

Ecological niche Individual Species Ecological nicheSocial system Person Institution SocietyBiological organism Cells Organs BodyBrain Neurons Regions Brain

language and cognition (?)...

... living systems


Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References

Interactions among and across scales


Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References

Evolution of complex systems

Conjuncture # 3: complex systems are nonlinear andmeta-stable therefore the focus on asymptoticbehavior does not help to understand them (better);

We want to focus on the process which guides thesystem from one metastable state to another;

I.e. their non-linear evolution and development;


Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References

Simulation modeling of scalable systems

Existing evolutionary models / theories:

niche construction[6];exaptation[5];punctuated equilibrium;generic cognitive development[4, 8];...

A goal: combine the existing theoretical approachesusing simulation modeling approach for developing ageneric computational model for simulating thedevelopment of a scalable system


Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References

The project

1 Generative computational model;

2 Simulation environment;

3 Simulation of a chosen system.


Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References

Generative computational model

The basis is the chemical reaction network theory andchemical organization theory[2, 3]

Each elementary agent in a system is represented as areaction of the form a + 2 ∗ b → 2c ;

Agents can receive or send information (’molecules’ fromvocabulary V = {a, b, c}) from or to other agents;

There is an underlying topological space so that agentscan self-organize in semi-stable sub-networks ofinteractions within reaction network[1];

Agents create / reinforce links with agents / ’reactions’which consume their products or supply the required’molecules’;

A sub-network of reactions = system of reactions = morecomplex reaction = a super-agent;

Super-agents react among themselves in the same(recursive) manner;


Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References


1 Distributed message-passing interface;Implemented on a JVM based Actor framework(GPars / Akka / Clojure?);

2 Topological spaceLinks between actors implemented as local memoryof actors;

3 Event loggingEvery event of the simulation produces a specialmessage with the timestamp, type,sourceagent, ...;

4 Analysis engineLive analysis of the streaming data (e.g. Ganglia,Nagios, etc.);Catching streaming data for reconstruction of thedynamic graph (on a graph database, e.g. Titan,Neo4J, Datomic...);Off-line analysis from snapshots of the graph (graphtraversal languages, e.g. Datalog, Gremlin, Cypher..)


Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References

Simulation of a social system

Individuals are modelled as systems of ’chemicalreactions’;

Institutions are emergent systems of reactions;

Interactions between institutions influence dynamicsof interactions between individuals and overalldynamics of the society.


Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References

What’s new

self-organization of fuzzy topological boundaries;

feedback loop between scales of a complex system;

computing system / big data analysis techniques;

....


Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References

Bibliography I

Peter Dittrich and Wolfgang Banzhaf. “ATopological Structure Based on Hashing -Emergence of a ”Spatial” Organisation”. In: FourthEuropean Conference on Artificial Life (ECAL97.1997, pp. 28–31.

Pietro Speroni di Fenizio. “Chemical OrganizationTheory”. English. PhD thesis. Germany: Universityof Jena, 2001. url:http://home.pietrosperoni.it/index.php/

research/ac/phd/.

Francis Heylighen. Chemical Organization Theory: aformalism for evolutionary cybernetics. July 2012.


http://home.pietrosperoni.it/index.php/research/ac/phd/

http://home.pietrosperoni.it/index.php/research/ac/phd/

Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References

Bibliography II

Robert Kegan. The evolving self: problem andprocess in human development. English. Cambridge,Mass.: Harvard University Press, 1982. isbn:0674272307 9780674272309 06742723159780674272316.

J. Mouret and S. Doncieux. “Evolving modularneural-networks through exaptation”. In: IEEECongress on Evolutionary Computation, 2009. CEC’09. 2009, pp. 1570–1577. doi:10.1109/CEC.2009.4983129.

F. John Odling-Smee, Kevin N. Laland, andMarcus W. Feldman. Niche Construction: TheNeglected Process in Evolution (MPB-37). en.Princeton University Press, Feb. 2013. isbn:1400847265.


http://dx.doi.org/10.1109/CEC.2009.4983129

Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References

Bibliography III

Maya Paczuski and Per Bak. “Self-organization ofcomplex systems”. In: arXiv preprintcond-mat/9906077 (1999).

David Weinbaum R. and Viktoras Veitas. “SyntheticCognitive Developoment: where intelligence comesfrom”. English. 00000. ArXiv, Dec. 2014. url:http://arxiv.org/abs/1411.0159.


http://arxiv.org/abs/1411.0159

Scale interaction

Viktoras, Marta


Scales

Scalable systems

Scale interactions


Simulation modeling


Computational model



What’s new

References

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WWCS2015 presentation

Science

Transcript of WWCS2015 presentation