FRE 2672

TFG Self-Organization - 01/07/2004

Engineering Self-Organization in MAS

Complex adaptive systems using situated MAS

Salima Hassas

LIRIS-CNRS

Lyon I University, France

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Outline

Introduction

Self-organizing Computing systems as self-organizing Situated MAS

Coupling to the environmentCo-evolution of social and spatial organizationsA complex adaptive system perspective

Some illustrations

Conclusion

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Introduction

Evolution of computing systems: High complexityComplex environments, sophisticated applicationsComplex data and usages/practices;Emergence of new needs, new practices, …

Computing system: a system open on its environment

Complexity of the environment: distributed, dynamic, evolving, uncertain, …

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Examples

Evolution of the Internet and the WebA complex dynamic network, exhibiting a self-organizing

character…

Evolution of Software EngineeringAwareness of dynamic changes of the environmentDesign at run-time

User more and more present User centered systemsCapture usages/practices through system use

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Issue

How to design computing systems exhibiting intelligence while embodied in their environment,

considered at its widest meaning?

Widest meaning:

physical as well as conceptual environment

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Issue

Environment is thus put at the heart of the engineering of the computing system

Conceptual environment related to uses (practices)Place of materialization of uses

(ex: Virtual communities)

Physical environmentPlace of materialization (embodiment) of the computing

system =>a complex network of resources

Place of inscription of traces of uses related to actions and interactions

=> Ex: web/Internet topology expresses usages

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Approach

The system is considered through its coupling with its environment

A double articulation:Physical articulation : Structural Coupling Conceptual articulation : Behavioral Coupling

Retroactive effects of one coupling on another Organizational articulation

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Implications on a MAS

Using Situated MAS to implement this kind of computing systems (complex systems aware of their environment)

The MAS is subject to the same coupling with its environment:

Structural Coupling : Physical articulationSpatial organization of the MAS / physical environment

Behavioral Coupling : Conceptual articulationSocial organization of the MAS / conceptual environment

Retroactive effects of one coupling on another Co-evolution of spatial and social organizations of the MAS

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Implications on a MAS

The design of the situated MAS must address

its spatial organization its social organization And the co-evolution of both organizations through the MAS dynamics

Self-organization is mandatory The eternal ants foraging example

Emergent Structures : shortest paths from nest to food sourcePhysical materialization of the spatial organization

Emergent behavior : self-catalytic frequentation of paths Conceptual materialization of the social organization

Self-organization is the mechanism which allows co-evolution of social and spatial organization

Need for a “glue” between both organizations : stigmergy mechanism

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Our vision

The computing system as a Complex Adaptive System A set of interconnected components (agents), strongly

interacting with one another at different levels :

Micro level: retroactive interactions between agents (local behaviors)

Macro level: emerging structure and organization of the system(global behaviors)

System Dynamics : maintaining the system organizationNon linear dynamic (retroactions and emergences)

Coupling to the environment: autopoïetic vision Co-evolution “structures-their generating processes”:

reflective loopCo-evolution of “spatial organization-social organization” in MAS

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Positioning

Self-Organizing Computing systems

Complex Adaptive Systems

Non Linear DynamicSystems

Situated Multi-Agents

General System TheoryCybernetics

Chaos Theory, statistical mechanics,..

Artificial lifeEmbodied intelligenceNature-inspired computing

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Propositions

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A Guiding framework

A framework for developing self-organizing computing systems:

Physical materialization of the environment and its spatial representation

A complex dynamic network of resources: importance of topology

Embodied Intelligence using situated agents Population of situated agents embodied in a physical (spatial) environment ==> incarnation of the computing system

StigmergySpatial structure for coding control and meta-control information

case of the electronic pheromone

Individual behaviors CorrelationStrategy: balancing exploitation (reinforcement) /exploration (diversity)

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Topology

Scale Free Networks and « small world » property

Scale freeSmall number of highly

connected nodes, distributed randomly

High number of nodes weakly connected

Small worldSmall average length between

any couple of nodes

Topology of networks produced by human activities / nature (exhibiting self-organization ..)

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Illustration

A computing ecosystem on the web: WACO system

A multi-agents system : An ecosystem composed of Web Ants (mobile agents),

mapped on the webUsing a social insects paradigm (stigmergy)

Combining foraging and collective sorting

Specialization/population regulation following the web content

Dynamics of population: Energy mechanism (order/disorder of web content)

(IEEE Swarm Intelligence 03 publication)

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Illustration

Experiment1 : Disorder decreasing

Disorder decreases while new

documents are created Disorder=number of scattered

documents Negative value of disorder : multiple

clustering of a same document

Scattered documents are those created(order emergence)

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Illustration

Experiment 2 : Clusters forming

Effectiveness of clustering Size of clusters increases regularly Sudden (small) decrease of mean

clusters sizes near time 80000Order emergence disturbed by new creations

Scattered documents are those created

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Illustration

Experiment3: Energy evolution

Energy evolution follows the disorder evolution Decrease near time 80000

=> order emergence

Decrease near time 100000 => new clustering operation:

specialists creation

order emergence

Specialists creation

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Illustration

Energy of specialized agents

Specialists energy increase during clusters forming

Near order emergence (near time 80000) energy = 0

Sudden increasing near time 100000, new clusters apparition

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Illustration

ECoNET Dynamic multi-criteria balancing on a network of processorsProblem:

On a network of processors, processes must find dynamically a spatial repartition allowing the satisfaction of the 4 following criteria :

Balancing the average of the perceived load

Spatial clustering of processes belonging to the same application (sharing of same data, resources)

Spatial clustering of processes belonging to highly communicating different applications (minimize communications delays)

Spatial repulsion of concurrent processes accessing the same resources (resources access conflicts)

Note

Environment is subject to perturbations and criteria may evolve during time..

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Conclusion

Towards a methodolgy of self-organizing computing systems

Environment : A central point for the systemSituated MAS paradigm: incarnation of the computing

system The MAS is subject to the same coupling with respect to its

environment

Deployment of the MAS in its physical environment : spatial organization

Maintaining the spatial organization through the social organization of the MAS

Retro-active effects of one organization on the other

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Conclusion

Necessary to study :Relation between spatial organization and the

environment topology (and their retro-active effects)Reflective coupling: structure-processes (autopoïesis)

Relation between spatial organization and social organization (and their retro-active effects)

Structure-environment coupling (self-organization)

Reflective effects between the two coupling Co-evolution of both (emergent) organizations and the

environment topology

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Thank you :))