FRE 2672
Engineering Self-Organization in MAS
Complex adaptive systems using situated MAS
Salima Hassas
LIRIS-CNRS
Lyon I University, France
TFG Self-Organization - 01/07/2004
Outline
Introduction
Self-organizing Computing
organizing Situated MAS
systems
as
self-
Coupling to the environment
Co-evolution of social and spatial organizations
A complex adaptive system perspective
Some illustrations
Conclusion
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Introduction
Evolution of computing systems: High complexity
Complex environments, sophisticated applications
Complex data and usages/practices;
Emergence of new needs, new practices, …
Computing system:
environment
a
system
open
Complexity of the environment:
dynamic, evolving, uncertain, …
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on
its
distributed,
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Examples
Evolution of the Internet and the Web
A complex dynamic network, exhibiting a self-organizing
character…
Evolution of Software Engineering
Awareness of dynamic changes of the environment
Design at run-time
User more and more present
User centered systems
Capture 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 environment
Place 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 articulation
 Spatial organization of the MAS / physical environment
Behavioral Coupling : Conceptual articulation
 Social 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 source
Physical 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),
interacting with one another at different levels :
strongly
 Micro
level: retroactive interactions between agents
(local behaviors)
 Macro level: emerging structure and organization of the system
(global behaviors)
System Dynamics : maintaining the system organization
 Non linear dynamic (retroactions and emergences)
Coupling to the environment: autopoïetic vision
 Co-evolution “structures-their generating processes”:
reflective loop
 Co-evolution of “spatial organization-social organization” in MAS
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Positioning
Non Linear Dynamic
Systems
Complex Adaptive
Systems
General System Theory
Cybernetics
Self-Organizing
Computing systems
Chaos Theory, statistical
mechanics,..
Situated Multi-Agents
Artificial life
Embodied intelligence
Nature-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
Stigmergy
Spatial structure for coding control and meta-control information
case of the electronic pheromone
Individual behaviors Correlation
Strategy: balancing exploitation
(diversity)
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(reinforcement)
/exploration
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Topology
Topology of networks produced by human activities / nature
(exhibiting self-organization ..)
Scale Free Networks
« small world » property
and
Scale free
 Small
number
of
highly
connected nodes, distributed
randomly
 High number of nodes weakly
connected
Small world
Small average length between
any couple of nodes
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Illustration
(IEEE Swarm Intelligence 03 publication)
A computing ecosystem on the web: WACO
system
A
multi-agents system : An ecosystem composed of
Web Ants (mobile agents),
mapped on the web
Using a social insects paradigm (stigmergy)
Combining foraging and collective sorting
Specialization/population
content
 Dynamics
regulation
following
of population: Energy
(order/disorder of web content)
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the
web
mechanism
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Illustration
Experiment1 : Disorder decreasing
 Disorder
decreases while
documents are created
 Disorder=number
of
new
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 80000
Order emergence disturbed by
new creations
Scattered documents are those created
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Illustration
Experiment3: Energy evolution
Energy evolution follows
disorder evolution
the
 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 processors
Problem:
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
computing systems
of
self-organizing
Environment : A central point for the system
Situated 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
environment topology (and their retro-active effects)
Reflective
the
coupling: structure-processes (autopoïesis)
Relation
between spatial organization
organization (and their retro-active effects)
Structure-environment
and
social
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 :))
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