CORMAS - P. Bommel

CORMASCORMAS

COMMON-POOL RESOURCES MANAGMENT

AND MULTI-AGENTS SYSTEMS

CORMAS - P. Bommel

What are we doing ?What are we doing ?

Development of an agent-based simulation

platform (CORMAS) dedicated to the field of

natural resources management

Test of a companion modelling approach

about how to use these types of models

Training courses, knowledge transfers

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Resource management and environmentResource management and environment

Social Dynamics

Biological Dynamics

Interactions

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A definition of complex systemsA definition of complex systems

Definition: Complex system : a set of elements interacting among them and

with the outside :• Distinction between the whole (the system) and the remainder

(environment/outer): reliance to the question

• Predominance of interactions : more than the sum of the parts.

Other characteristics: Descriptions at multiple levels (a minima: elements / system) Emergence Structures making

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Approaches of complex systemsApproaches of complex systems

Analytical : element by element (neo-classical economy, plot, individual, etc.)

Holistic or systemic : global behaviour of the system (macro-economy, statistics)

Constructivist : articulation between individual behaviours of the elements (local) and the global behaviour of the system (global).

Suitable to study ecosystems and sociosystems

Challenge of complexity : situations far from equilibrium

Intelligibility : intuitive description in terms of objects and agents

rather than variables and equations

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Example: fish reproduction

Analytical :

• Behaviour of one fish

Holistic :

• Schaefer model

Constructivist :

• Each entity of the system is represented (Molecule, cell, plant,

animal, group, etc.).

• Reproductive behaviour => evolution of the population

• Interactions between entities (Modification, creation,

destruction)

• Local interactions (reproduction with neighbours) => spatially-explicit

model

Approaches of complex systems (2)Approaches of complex systems (2)

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Why consider the individual?Why consider the individual?

Principle of individual uniqueness Mathematical models assume that individuals are

indifferent and interchangeable (exchange of two

individuals randomly chosen in the population)

Weakness of the mixing hypothesis: the differences

between individuals drive evolution of systems

Principle of located interactionsAn organism is mainly affected by the other organisms

and by the environmental conditions in its spatio-

temporal neighbourhood

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Why consider the individual?Why consider the individual?

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The essence of complexityThe essence of complexity

Interactions and viewpoints

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Complexity Complexity and resources managementand resources management

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PostulatesPostulates

Individual and collective processes

dealing with natural resources

management are based on:Shared representations of interactions between

stakeholders and the ecosystem.

Towards modelling to :Articulate multiple viewpoints ;

Articulate multiple levels (from local to global) ;

Allow retrospective and prospective analyses ;

Be understandable by the stakeholders.

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Modelling Modelling and collective dynamicsand collective dynamics

Environment(common-pool

resources)

??

?

?

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Environment(common-pool

resources)

?

?

Shared representations of interactions between Shared representations of interactions between stakeholders and the ecosystemstakeholders and the ecosystem

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An explicit representation of space An explicit representation of space

Some elements from CORMAS facilities

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CORMAS: CORMAS: an agent-based simulation frameworkan agent-based simulation framework

Origin: the aggregation of MA models experiments dedicated to the domain of natural-resources management

Cormas is an agent-based simulation framework

It is oriented towards the building of simulation modelsa programming environment.

It provides a framework for developing simulation models of coordination modes between individuals and groups that jointly exploit common resources.

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Common-pool Resources and Multi-Agent Systems

http://cormas.cirad.fr

CORMAS web siteCORMAS web site

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DB, GIS Cellular automata

Environment containing resources, a topographic support

SpatialiSpatialissed multi-agent systemed multi-agent system

Spatial objects: points of view

Agents using or managing resources

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Each agent builds its own representation ofEach agent builds its own representation of the the environmentenvironment

Spatial grid

DB, GIS Cellular automata

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Spatial Spatial hierarchy levelshierarchy levels

Various ways of segmenting the space

Relations of composition between spatial

entities can define several hierarchical

levels

On which entity to associate the

processes of the dynamics of the

landscape ?

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Spatial Spatial hierarchy hierarchy levelslevels

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The basic levelThe basic level

The Cell = the spatial entity element

The grid = a network of automatons

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The basic level: The basic level: Regular tessellationRegular tessellation

MooreVan Neumann

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The basic level: The basic level: Regular or Irregular tessellationRegular or Irregular tessellation

From GIS (Raster and Vectorial mode)

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The basic level: The basic level: Regular tessellationRegular tessellation

From GIS data (Raster mode)

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The basic level: The basic level: Vectorial modeVectorial mode

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TheThe aggregation aggregation levellevel

Spatial entities as agents’ viewpoints

Aggregation as reification of POV

Example of aggregation with minimum size

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HerbShrubTreeRock

Representation Representation of a of a MediterraneanMediterraneanforestforest

Forester’s

viewpoint

Shepherd’s

viewpoint

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Same hierarchSame hierarchyy structure for polygonal spatial structure for polygonal spatial entities (vectorial mode) entities (vectorial mode)

Elementary entities Cultivated plots

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Ecological dynamicsdefined at the basic level

Agricultural dynamics defined at the level of the plots

Some dynamics are strongly related to a specific Some dynamics are strongly related to a specific hierarchical level hierarchical level

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Spatial object dynamics Spatial object dynamics

Spatial index calculation

spatial dynamics

influence modify

generateproduce

Human strategies:pasture, grubbing, clearing

Natural processes :growth, dissemination of

vegetation

Shapesof

spatialobjects

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Check

Biggest forest

Fire-break

Clear max Brushwood

Protect grassland

Level 0 strategies

Level 1 strategies

Spatial strategiesSpatial strategies

compact grassland

Biodiversity

Landscape

Level 2 strategies

Level 3 strategies naturalist

shepherd

Let Nature works

shepherd

forester

farmer

naturalistforester

tourism’sprofessional

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carryingCapacity=2 grid Size: 50x50

Initial nbOfPreys=1000 Initial nbOfPredators=70

0

500

1000

1500

2000

2500

3000

3500

0 200 400 600 800 1000 1200 1400 1600 1800 2000

0

50

100

150

200

250

300

350

400

450

500

nbPreys

nbPredators

Exemple: PursuitExemple: Pursuit

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ApplicationsApplications

Standard modelsGame of life (Conway)

ECEC: Evolution of Cooperation (Pepper and Smuts)

SPD (Nowak and May)

SugarScape (Axtell and Epstein)

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ApplicationsApplications

Applied models [AWARE] : Agent-based Watershed Analyses for Resource and Economic

Sustainability in South Africa (Farolfi).

[AutomateVote] : electoral ballot

[Bohol] : Natural Resource Management of the Municipality of Loon in Bohol, Philippines (Campo).

[BrouteLaForêt] : spatial representations and interactions between individuals, space and society (Bonnefoy).

[Burkina] : soil quality indicators in Burkina Faso (Guillobez).

[CatchScape] : River bassins management in north Thaïland (Becu, Perez, Walker)

[Didy] : multiple uses of a forest ecosystem in Madagascar (Abrami).

[Djemiong] : hunting of wild meat in Cameroun (Le Page, Bousquet and Bakam).

[Dricol] : emergence of resource-sharing conventions (Thébaud and Locatelli).

[Echos] : Economic behaviour analysis of the "Stockbreeding wastewater system" actors at the Reunion Island (Farolfi, Bommel).

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ApplicationsApplications

Applied models [FauconColombe] : game theory and prey-predator model (Valeix).

[FiliereRaphia] : raphia marketing system in Madagascar (Herimandimby, Randriarijaona, Bousquet and Antona).

[ForPast] : spatial transformations dynamics of sylvopastoral systems (Lardon and Bommel).

[Gemace] : multiple uses of wetlands in Camargue, France (Mathevet).

[JLB] : spatial transformations dynamics of forest systems (Bonnefoy).

[JuMel] : economic exchanges and emerging organizations (Rouchier).

[Kayanza] : firewood in Burundi (Guizol, Ndikumadengue, Bousquet and Antona).

[MagmaS] : exchange of stock-farm effluents in Reunion island (Martin, Piquet, Le Page and Guerrin).

[Markets] : Assessing the performance of different market institutions in West Africa according to communication systems (Galtier).

[Mejan] : pine encroachment of natural ecosystems in Lozère, South of France (Etienne and Le Page).

[Mobe] : regulation of firewood marketing systems in Niger (Martine Antona).

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ApplicationsApplications

Applied models [Nong Chok] : Land use change in a peri-urban area, Bangkok Thailand (Anwar

and Borne).

[Orizi] : Small irrigation systems under free management (Perez and Becu).

[Pasteur] : sparse resource sharing by herds in sahelian area (Bah and d'Aquino).

[PlotsRental] : plot renting by individual contracts or by centralized auction system (Bousquet and Le Page).

[Potlatch] : economic exchanges and emerging organizations (Rouchier).

[Sabah] : plantation development among small farmers in Malaysia (Guizol).

[SaintGeorges] : pasture and overgrowing brushwood in a village of Lozère, France (Lieurain).

[Samba] : land use in North VietNam (Boissau, Jean-Castella).

[SavaneAgents] : landscape dynamics, agent-based version (Gautier and Bousquet).

[SeaLab] : homing-like reproductive strategies (Le Page).

[Sinuse] : distributed interactions between an underwater table and its users (Feuillette).

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ApplicationsApplications

Applied models [SpatioDyn] : spatial dynamics modelling with GIS and MAS (Bonin and Le Page).

[Spiders] : net building by social spiders, a model from Bourjot and Chevrier.

[Stratagènes] : negotiation for phytogenetic resource local management in

Madagascar (Aubert and Le Page).

[SylvoPast] : Sylvopastoral management and wildfire prevention in Mediterranean

forests (Etienne and LePage).

[WsErosion] : soil erosion risk and agricultural diversification in a Northern-

Thailand watershed

[Zambeze] : land-use dynamics in the Zambeze valley

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FutureFuture … …

A community of 200 users

Interactive simulation => RPG and Cormas

Distributed interactive simulation

Towards a “Companion” Modelling Approach

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Models and usersModels and users

Passive way : Simulation models are frequently used in a passive way, presenting

only the results of experiments performed with the model.

Sensitivity analysis: People who experience the system dynamics will yield a better

understanding of the model.

Interactive simulation : In a simulation game like Fishbanks (Meadows, 1989) the players make

decisions about fishing strategies and the computer computes the fish

catches. The players have only limited control over the environment.

A “Companion” Modelling Approach : Combining ABM and RpG