swarmfest - panarchy theory

7/27/2019 SwarmFest - Panarchy Theory

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Proposing Panarchy Theory as a synthesis and

validation mechanism for ABM models of

Sociological & Ecological Systems

SwarmFest 2013

Fahad Ahmad Khan Ivan GaribayUniversity of Central Florida


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The Goal Here is to

Panarchy as Meta-Stylized Fact for Complex Adaptive Systems

simulation (specifically in Sociological and Ecological studies)

Devising Mechanisms, Algorithms, ABM Agent Rules for the

observance of Panarchy in simulations


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What does Panarchy Explain

Panarchy theory represents the evolution of complex

adaptive systems in three dimensional space -

potential, connectivity & resilience

It is a qualitative description of the adjustment or

adaptation of systems to change in external

environment


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Why is Panarchy deemed useful

Itsa meta-model which helps to explain resilience of

systems in terms of evolutionary network dynamics

such as potential and connectedness

Resilient systems by definition should be able to

adapt and adjust to unforeseen events, to absorb

change and learn from diversity

It is widely accepted with only few counter examples


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How does Panarchy work

The Adaptive Cycle

There are four phases in the Panarchy model through

which a function of the three variables should

periodically cycle

The phases are Exploitation, Conservation, Release &

Reorganization

The variables are Potential, Connectedness &

resilience


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Panarchy Phases

Exploitation (r):Also referred to as the birthphase. This stage is oneof rapid expansion. Pioneer and opportunist species proliferate, building

up biomass and greater connectedness. Therefore, in this stage,

connectedness and stability increase. In ecological terms, this stage occurs

when a population finds a fertile niche in which to grow.

Conservation (K): Also referred to as the growth and maturationphase. This is a stage of slow accumulation and storage of energy and

materials. Here, the biological capital is stored and connectedness reaches

its peak. In ecology this stage occurs when a population reaches itscarrying capacity and stabilizes for a time.


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Panarchy Phases

Release (): Also referred to as the death phase. This stage occursrapidly in a system that has become over-connected. The release of storedcarbon and nutrients is triggered and causes quick and drastic changes. Inecosystems this stage occurs when a population declines due to acompetitor or changed conditions.

Reorganization ():Also referred to as the renewalphase. This stagecan also occur rapidly, where the system renews itself or flips into anotherstate. This new state may be less productive and organized than theprevious state. The reorganization phase is characterized by weak

connections, weak organization and weak regulation, and is considered tobe the most unpredictable stage. In ecological terms, during this stagecertain members of a population are selected for their ability to survivedespite competitors or changed conditions that triggered the release.


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Phases in the Adaptive Cycle


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The Normal Route in an Adaptive Cycle


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Routes for Poverty and Richness Traps


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Panarchy Variables

Potential

Potential means the possibility of novelty in the system. A roughanalogue would be information content in the system.

ConnectivityConnectivity implies the richness of links between interacting entitles inthe system. In terms of graph theory the it translates into density ofedges between vertices (or links between nodes in Network Theory).

ResilienceResilience is the capability to withstand shock without catastrophicfailure


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weak strong

low

high

2-D View of Panarchy


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The space between consecutive arrow-heads is a qualitative

indicator of the speed of the transition through phases


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Conservation


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Release


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Reorganization


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Exploitation


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The Complete Adaptive Cycle


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Examples

Functional Typology

Adaptive Cycle r K

Ecosystems Exploitation Conservation Release Reorganization

Economics Entrepreneurship Saturation /

Monopolism

Creative

Destruction

Innovation

Organizations

&

Bureaucracies

Structuration Consolidation Breakdown /

Revolt

Reformation

Exploitation Exploration


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http://scienceprogress.org/2011/05/waves-of-innovation-2/
http://scienceprogress.org/2011/05/waves-of-innovation-2/http://scienceprogress.org/2011/05/waves-of-innovation-2/http://scienceprogress.org/2011/05/waves-of-innovation-2/http://scienceprogress.org/2011/05/waves-of-innovation-2/http://scienceprogress.org/2011/05/waves-of-innovation-2/http://scienceprogress.org/2011/05/waves-of-innovation-2/http://scienceprogress.org/2011/05/waves-of-innovation-2/http://scienceprogress.org/2011/05/waves-of-innovation-2/


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There are already models that show how to increaseconnectedness so the network follows power-laws e.g.Preferential Attachment by Barabasi]

For Panarchy Jain and Krishnas model of Network Growthusing Autocatalytic Sets is better because it also has diversityin terms of node roles and a mechanism for replication &differential fitness (competition) along with adherence topower-laws

Replication, Variation (Mutation) and Differential Fitness(Competition) guarantee evolution according to DanielDennett

Panarchy for ABMs


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Their model exhibits the Punctuated Equilibrium

phenomenon which is another word for periodic self-

organization after system crashes

Thus their model exhibits Panarchy in a Stylized manner

Sand Pile models exhibit a stylized form of Panarchy but they

only have dynamics of self-organization and no evolution

Panarchy for ABMs


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Panarchy for ABMs

Stefan Thurners model revolves around the mechanism of

species recombination and this results in triggers

Both Stefan Thurner and Krishnas models have exogenous

forces for triggering extinction events and no dissipative

mechanisms for death

It would be interesting to see if endogenous mechanisms such

as inhibiting feedbacks in the network could be devised for

these triggers


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Goals

Panarchy as Meta-Stylized Fact for Complex Adaptive Systems

simulation (specifically in Sociological and Ecological studies)

Devising Mechanisms, Algorithms, ABM Agent Rules for the

observance of Panarchy in simulations


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Conclusion

Panarchy could act as a unifying mechanism for synthesisand validation of Agent Based Models for Sociological and

Ecological Systems


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Questions


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Complexity

A Generative Network approach for Complex Adaptive Systems

Dynamic Networks

Genetic Algorithms

Using Panarchy Theory to devise Genetic Algorithms

A better paradigm for search in Genetic algorithms

May result in development of adaptive controllers i.e. controllers that adapt their

transfer function in response to continuously changing stimuli/environments


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Increase in Novelty/Information/Innovation increases the width of the attractor basin for the

next adaptive loop, thereby, increasing the resilience and stability of the system for the next

adaptive cycle


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Devise/Discover/Suggest mechanisms for the entry and exit of the system state through

various phases of the adaptive

Evaluate what would lead the system to go form the back loop into the forward loop i.e.

from reorganization and then growth to consequently conservation and eventually

release

For Example, what is the mechanism for the punctuated equilibrium can be observed

when the system goes from conservation to release

Meta-Stylized fact for ABM simulations of socio-ecological systems

swarmfest - panarchy theory

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