Apr 5, 2011 - 2007), rill grow (Favis-Mortlock, 1996), landslides (Hergarten and Neugebauer,. 1998 ... A common CA language ... A common MAS language.
Tuesday, 05 April 2011 Simplicity and complexity in evolution of coupled geomorphic systems: concepts, models and applications
Cellular automata (CA) and Multi-Agent Systems (MAS) to better assess complex environmental problems: a review on French research over the last ten years Johnny DOUVINET 1 , Cyril FLEURANT 2, Daniel DELAHAYE 3, Sébastien CAILLAULT 3, Vincent VIEL3 , Philippe ELLERKAMP 1 1
University of Avignon, UMR ESPACE 6012 CNRS, Avignon, France AgroCampus Ouest, Landscape Unit Research, Angers, France 3 University of Caen, UMR LETG 6554 CNRS, Caen, France
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1. Formalism and applications of CA models
CA emergence Definition: “a discrete model consisting in a infinite, regular grid of cells, each in one of a finite number of states” (Von Neumann, 1966) Objectives: local and simple interactions between cells (with simple rules) to produce complex, multiscalar and global behavior (Wolfram, 1983, 2005)
Complex pattern observed with a simple local rule : a cell changes its state (i) at the next iteration (i+1) when i+1 is present in 3 cells-neighborhood (adapted from Griffeath, 2003)
Applications in “physical geography” Numerous initiatives since the 1990s: fluvial eroded landscape (Chase, 1992), sorted stone stripes (Werner and Hallet, 1993), braided channel patterns (Murray and Paola, 1994), aeolian dunes (Werner, 1995; Thomas and Nicholas, 2007), rill grow (Favis-Mortlock, 1996), landslides (Hergarten and Neugebauer, 1998; Macklin, 2002; Van de Wiel et al., 2010), lava dynamics (Avolio et al., 2006), geomorphology-hydrology (Fonstad, 2006) >> and many others !
Effects of one flood (with a peak discharge of 100m3/s) on sediment and eroded sediments on 2 kilometers of the river Teifi using the CAESAR model (Coulthard et al., 2007)
A real but late interest in France Initiatives since the 2000s: runoff modeling (Delahaye et al., 2001), erosion or sedimentation dynamics (Crave and Davy, 2001), fine-scale runoff process (Valette, 2006), dune patterns (Narteau, 2006), fluvial vegetation (Corenblit, 2008) >> Numerous applications but 10 years after Anglo-saxon applications >> French geographers use the CA models for urban topics since the 1990s
Dynamics of runoff within a dry valley, integrating rainfall inputs, land use cover and relief derived from the Numerical Model of Topography (Delahaye, 2001; Douvinet et al., 2007)
2. Formalism and applications of MAS models
MAS emergence Definition: “They specify automata states, especially transition rules in a way that enables interpretation of autonomously behaving agents” (Maes, 1995) Objectives: taking into account basic entities and the relationships between it as agents/agents or agents/environment (Weis, 1999)
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Unique lyer
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Multi-lyers
Micro ð macro (simulation)
Micro ó macro (self-organized systems) Emergence of MAS derived from CA and Artificial Intelligence (Troitzsch, 1997)
Applications in “physical geography” Specific applications with decision making processes since the 1990s: land use change (Openshaw, 1994, CIRAD, 2001), evolution of landscape (Epstein and Axtell, 1996, Ménard et al., 2001) >> environment becomes gradually important as it plays a key role on decision-making processes…
Scheme for simulating the evolution of complicated land use systems based on multiagents in China – results obtained at several iterations (Liu et al., 2006)
Rapid applications but specific projects in France First initiatives in the 1990s: soils glutted with water (Perrier et al., 1995), hydrological fluxes (Drogoul, 1995), sediment deposition (Teles et al. 1999) Recent applications: water balance (Bécu et al., 2008), multi-termite model (Fates and Chevrier, 2010), surfaces destroyed by fire (Caillault, 201#)
Simulation of surfaces destroyed by fire during one year taking into account climatic variables at regional scales and propagation of fire according simple rules (Caillault, unpublished !)
3. Different applications but constant similarities…
A common CA language Rules according to the traditional formalism: regular mesh (square, triangular or hexagonal), finite number of possible states, iterative process in time, static and non-changing transition rules (Weisbuch, 1999 ; Wolfram, 2002) >> cellular unit is post-pounded by the relations between cells
Hexagonal mesh to improve fire diffusion in one alluvial floodplain in the CA SpaCells (Langlois, 2002)
Triangular mesh to simulate hydrological process in the CA RuiCells (Douvinet, 2008)
A common MAS language Rules according to the ODD standard protocol (Grimm et al. 2000): Overview (purpose, state variables and scales, process overview and scheduling), Design concept (emergence, interaction, sensing, stochasticity), Details (initialization, inputs, sub-models) >> readers are guided by their expectations
Input parameters, virtual city and ouput data used in the TOXICITY model (Salze et al, 2010)
Common modifications for geographical assessment Structure: finite elements, cells with variable forms and dimensions.. Neighborhood: enlarged (until more than 100 cells) Transition rules: probabilistic to take into account variability of systems >> do we have to change the name of original CA or MAS models ?
Comparison between SWAN model (left) and parameterized model (right) wave heights for 15m/s wind in Liverpool bay (Project CEMCOS)
A common framework to intuitive programming Important details: fine-resolution in time and space (>> links with GIS) Testing hypothesis: experimentations are not always easier (floods, fires…) Simple models: easy to understand, easy to implement >> systems become more and more complex (Is it the real objective ?)
Runoff simulation obtained with RuiCells on A) a small parcelar unit using a numerical model with 1m-length and B) a small basin using location of cultivated areas (Douvinet, 2008)
A common approach for reducing complexity Empiric rules: observations guide implementation of transition rules Specific patterns: emergence of non-attempted phenomena, importance of scales, spatial interactions within self-organized systems… >> we do not enter in a complicated modeling !
Using RuiCells and simple rules, we detect in some basins points of energy, where important runoff can be concentrated in a short time (Douvinet, 2008)
4. Supports and challenges : How can we improve the use of these successful tools in the future ?
Increasing our attention more on MAS than on CA models? Critics on CA : challenges if incorporating human decision making (Parker et al., 2003; Torbey, 2009); state of cells conditioned by neighborhood (Daudé, 2003); bottom-up approach without top-down possibilities (Sanders, 2000) >> Models tested unsuccessfully = CA more adapted for physic process… >> AC replaced or coupled with MAS models, one utopia!
Numerical modelling on a parcelar unit showing impacts of tracks on soil (Chartin, 2008)
Required coupling with other models? Smoothed particle models: hydrodynamic phenomena (Van de Wiel, 2007) Physic-based models: hydrophysic components (Malet, 2003; Fleurant, 2008) >> sensing and multi-disciplinary approaches to better assess complexity >> comparative analysis to improve results obtained with simple rules
Numerical modeling of geomorphic evolution of karts in cokpit: the example of Cockipt Country, Jamaïqua (Rochereau, 2007; Fleurant, 2008)
Conclusion
► Let’s reminding a few results ► CA and MAS models have been differently applied in France ; therefore,
increasing attention on these tools (even late!) reveals high interests ► Two types of languages exist but similarities are easier understanding ► CA are used more frequently for physic phenomena (and coupling with physic-based or smoothed particle models) than MAS models
► Future challenges ► Coupling CA and MAS models should be a great opportunity but not for
all the topics (example : displacement of persons during flash flooding) ► Comparing European and International approaches over the last ten years to define advantages, difficulties and evolution of CA and MAS
Tuesday, 05 April 2011 Simplicity and complexity in evolution of coupled geomorphic systems: concepts, models and applications
Cellular automata (CA) and Multi-Agent Systems (MAS) to better assess complex environmental problems: a review on French research over the last ten years Thanks for your listening !! Hope you envoyed Johnny DOUVINET1 , Cyril FLEURANT2, Daniel DELAHAYE3, Sébastien CAILLAULT3, Vincent VIEL3 , Philippe ELLERKAMP3 1
University of Avignon, UMR ESPACE 6012 CNRS, Avignon, France AgroCampus Ouest, Landscape Unit Research, Angers, France 3 University of Caen, UMR LETG 6554 CNRS, Caen, France
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