Roger MARTIN-CLOUAIRE holds a Masters in Biomedical Engineering (1982) from Saskatchewan University (Canada) and a PhD (1986) in Artificial Intelligence (AI) from Toulouse University. His research works in these graduate student years focussed primarily on developing and implementing possibility theory models of approximate reasoning in knowledge-based systems.
He joined INRA (Institut National de la Recherche Agronomique) in 1987 as a research scientist in the newly created computer science department of INRA. He was the director of the laboratory Unité de Biométrie et Intelligence Artificielle (former MIAT) from October 2006 to the end of 2010.
Main area of work
Central theme = modelling and simulation of intelligent agents involved in production management tasks
The relevance of simulation approaches to the study and design of agricultural production systems is widely claimed. The methodology and computer software appropriate to such a task have still not reached the state of a mature technology and are mainly developed in research laboratories. Suitable computer models need to represent the structure and dynamics of the underlying biophysical system together with the coordinated human activities involved in the management of the farm production process. Production process improvement involves studying interactions among biophysical processes and decision making processes at the farm level while most existing approaches tend to address one at the expense of the other: the human actor is part of the feedback process, not standing apart from it.
The objective to enhance modelling & simulation capabilities to meet the system research needs yielded to the development (in collaboration with J-P Rellier) of DIESE, a framework especially designed for building and running agricultural production system models. The classical approach to representing decision making in simulation models is to express decision behaviour through a set of decision rules. This approach becomes cumbersome as the number of rules grows beyond a threshold; the meta knowledge about the proper use of the rules (e.g. which should be applied first when several are applicable) is hard to represent and makes the rule-base hard to maintain and reuse. By contrast DIESE relies on a much richer conceptual basis under the form of an ontology of agricultural production systems. It supports the modelling of the decision process in terms of activities, resources required to realize them, and well-structured constraints bearing on the relevance and feasibility of activities, the interdependencies between them and the restrictions on the uses of resources.
Computationally the ontology comes under the form of a C++ library. In developing a farm production system model, the ontology acts as a metamodel; implementing a model amounts to particularizing the ontology concepts as required by the domain and then instantiating the corresponding classes to capture the specific aspects of the system to be simulated. A discrete event simulation mechanism realizes the step by step interpretation of the strategy and the progressive execution of the decided activities, which in turn alter the biophysical state that, otherwise, changes only in response to external factors such as weather.
DIESE is currently used in large modelling projects dealing with various kinds of production such as cash crop, vineyard, pasture-based livestock and pig systems. The development of the ontology was largely inspired by the analysis made in a modelling project on greenhouse tomato production systems. These projects attest to the wide scope of applicability of the framework.
Study of farmers’behavior in making operational decisions
Ph.D. thesis of C. Daydé (december 2013-december 2016):
The thesis proposal focuses on how a farm manager is making operational decisions (choice of actions). It involves characterizing and formalizing the types of information used in the decision-making process and investigating the mechanisms by which they are manipulated and by which constraints, desires and judgement are combined. In order to enable an experimental investigation of such behavior considered as a research object the thesis work should ultimately provide a general and implemented model of the decision process, hopefully covering the variety of decision-making behaviors identified. To be faithful to the reality, the choice has to be done with little processing in order to be compatible with the paucity of information and the fast pace of decision-making observed in farmers’ practices. The investigation dwells on a body of approaches having their roots in qualitative decision, bounded rationality and behavioral economics. For more details see Investigating operational decision-making in agriculture. See also Modelling operational decision-making in agriculture for a BDI-based modelling approach.
Methodology of participatory design approaches with application to the adaptation of livestock systems to climate change
FARMATCH project: The diversity and complementarities of spatio-temporal production patterns and products in livestock systems (ranging from grassland-based to mixed-crop systems) are potential assets to dampen the effects of climatic variability and to adapt to changing climatic or economic contexts. Unfortunately what seems to improve the robustness and efficiency of a livestock system (or reduce its vulnerability) is at the same time increasing its complexity due to the need to manage dynamically several processes that interact in space and time. The main objectives of the FARMATCH project are to:
- analyse adaptation made by livestock farmers in the past and develop a model-based method to assess exposure to climate change and variability;
- develop and diffuse a participatory framework that can support the design of livestock systems adapted to particular climatic, economic, technical, environmental and social aspiration factors.
The workshop-based design framework involves farmers and/or advisors and researchers. Through such workshops the design process exploits intertwining of scientific knowledge and experiential and tacit knowledge of the farmers and advisors. Vulnerability and sustainability (economic and environmental in particular) of the designed systems are assessed thanks to various kinds of models that are also used to convey efficiently knowledge and ensure that a common basis is shared among the participants. The project is structured into 3 WPs: 1- Characterizing vulnerability, 2- Generic principles governing participatory and model-based redesign, and 3- Experimentation with and diffusion of the participatory design framework. See http://dx.doi.org/10.1016/j.jenvman.2017.02.050.
Supporting the acquisition and communication of practical knowledge in agroecology and ecosystem services
A farm system is not simply a collection of crops and animals to which one can apply simple management rules and expect immediate results. Rather it is a complicated interwoven mesh of soils, plants, animals, workers, other inputs and environmental influence that are manipulated by the farmer who, given his knowledge, preferences and resources attempts to achieve his aspirations. Agroecology is a scientific discipline that uses ecological theory to study, design, manage and evaluate agricultural systems that are productive but also resource conserving. The growth of practical knowledge about the production, maintenace and exploitation of ecosystem service is essential toward the implementation of agroecology. This depends largely on the accumulation and organization of information produced by experimental or descriptive research and monitoring activities. Farmers have a key role to play in this “integrative approach” where progress is achieved through the integration of experiential knowledge from different domains (crop, animal, ecology, management,business). A continual learning process must be put in place and the most efficient methods available used to inform this process.See Ontological foundation of ecosystem services and the human dimension of agroecosystems.
Past topics of interest at INRA
- Constraint satisfaction with soft and/or uncertain constraints
- Planning under uncertainty with nondeterministic actions
- Handling uncertainties in regional soil maps
- Management problems in agricultural production systems
- constraint satisfaction applied to the daily determination of climatic setpoints in greenhouse tomato production
- rotational grazing in grassland-based livestock systems
- work organisation in cropping systems and vine growing systems
Some recent papers
R. Martin-Clouaire. Knowledge elicitation and modeling of agroecological management strategies. 2020. To appear (available on request).
R. Martin-Clouaire. Ontological foundation of ecosystem services and the human dimension of agroecosystems. Agricultural Sciences, 9, 525-545, 2018.
R. Martin-Clouaire. Modelling operational decision-making in agriculture. Agricultural Sciences, 8, 527-544, 2017.
M. Sautier, M. Piquet, M. Duru, R. Martin-Clouaire. Exploring adaptations to climate change with stakeholders: A participatory method to design grassland-based farming systems. Journal of Environmental Management, 193, 541-550 http://dx.doi.org/10.1016/j.jenvman.2017.02.050, 2017.
R. Martin-Clouaire, J.-P. Rellier, N. Paré, M. Voltz, A. Biarnès. Modelling Management Practices in Viticulture while Considering Resource Limitations: The Dhivine Model. PLoS ONE 11(3), http://dx.doi.org/10.1371/journal.pone.0151952, 2016.
M. Duru, M. Benoit, J.-E. Bergez, M.-H. Jeuffroy, E. Justes, G. Martin, R. Martin-Clouaire, J.-M. Meynard, H. Ozier-Lafontaine, L. Prost, B. Rapidel, Q. Toffolini, J.-P. Sarthou, O. Therond. Bridging the gaps between ecological principles and actions for designing biodiversity-based agriculture. Presented at Farming systems design 2015, Montpellier (Sept. 7-10).
C. Daydé, S. Couture, R. Martin-Clouaire. Interview-based structuring of operational decision-making by farmers. Presented at Farming systems design 2015, Montpellier (Sept. 7-10).
M. Duru, O. Therond, G. Martin, R. Martin-Clouaire, M.-A. Magne, E. Justes, E.-P. Journet, J.-N. Aubertot, S. Savary, J.-E. Bergez, J.-P. Sarthou. How to implement biodiversity-based agriculture to enhance ecosystem services: a review. Agronomy for Sustainable Development, 35(4), 1259–1281, 2015, http://link.springer.com/article/10.1007/s13593-015-0306-1.
F. Lescourret,D. Magda, G. Richard, A.-F. Adam-Blondon, M. Bardy, J. Baudry, I. Doussan, B. Dumont, F. Lefèvre, I. Litrico, R. Martin-Clouaire, B. Montuelle, S. Pellerin, M. Plantegenest, E. Tancoigne, A. Thomas, H. Guyomard, J.-F. Soussana. A social–ecological approach to managing multiple agro-ecosystem services. Current Opinion in Environmental Sustainability, 14, 68-75, 2015. (doi:10.1016/j.cosust.2015.04.001)
V.O. Snow, C.A. Rotz, A.D. Moore, R. Martin-Clouaire, I.R. Johnson, N.J. Hutchings, R.J. Eckard. The challenges and some solutions to process-based modelling of grazed agricultural systems. Environmental Modelling & Software, 62, 420–436 http://dx.doi.org/10.1016/j.envsoft.2014.03.009, 2014.
M. Sautier, M. Piquet, M. Duru, R. Martin-Clouaire. A sequential participatory approach to adapt livestock to climate change. Proc. 7th Congress on Environmental Modelling and Software, (IEMSS2014), San Diego. 2014.
C. Daydé, S. Couture, F. Garcia, R. Martin-Clouaire. Investigating operational decision-making in agriculture. Proc. 7th Congress on Environmental Modelling and Software, (IEMSS2014), San Diego. 2014.
P. Carrère, R. Delagarde, J.-C. Emile, M. Lherm, R. Martin-Clouaire, M. Tichit, S. Plantureux. Quelles stratégies de recherche pour favoriser l'émergence de systèmes fourragers innovants ? Fourrages, 217, 57-68, 2014.
M. Sautier, M. Duru, R. Martin-Clouaire. Use of productivity-defined indicators to assess exposure of grassland-based livestock systems to climate change and variability. Crop and Pasture Science, 64(7), 2013.
M. Sautier, R. Martin-Clouaire, R. Faivre, M. Duru. Assessing climatic exposure of grassland-based livestock systems with seasonal-scale indicators. Climatic Change, 120(1-2),341–355, 2013.
M. Sautier, R. Martin-Clouaire, M. Duru. Caractérisation du changement et de la variabilité climatiques en vue de l'adaptation des systèmes fourragers à base d'herbe. Fourrages, 215, 201-209, 2013.
G. Martin, R. Martin-Clouaire, M. Duru. Farming system design to feed the changing world. a review. Agronomy for Sustainable Development, 33,131-149, https://link.springer.com/article/10.1007/s13593-011-0075-4, 2013.
G. Quesnel, M. Akplogan, M. Bonneau, R. Martin-Clouaire, N. Peyrard, J.-P. Rellier, R. Sabbadin, R. Trépos. Décision dans les agro-écosystèmes. Revue d'Intelligence Artificielle 27(4-5), 409-442, 2013.
S. Couture, R. Martin-Clouaire Towards a better understanding of operational decision making in agricultural production systems. 4th Int. Symp; for Farming Systems Design, Lanzhou, China, 2013.
X Chardon, C Rigolot, C Baratte, S Espagnol, C Raison, R Martin-Clouaire, J-P Rellier, A Le Gall, J-Y Dourmad, B Piquemal, P Leterme, J-M Paillat, L Delaby, F Garcia, J-L Peyraud, J-C Poupa, T Morvan, P Faverdin. MELODIE: a whole-farm model to study the dynamics of nutrients in dairy and pig farms with crops. Animal, 6(10),1711-1721, 2012.
M. Sautier, G. Martin, R. Martin-Clouaire, M. Piquet, M. Duru. Participatory design of livestock systems adapted to new climatic conditions. The 10th European IFSA Symposium. Aarhus, Danemark, pp 1–9.2012
M. Sautier, R. Martin-Clouaire, M. Duru. An intelligible assessment of climatic exposure of grassland-based livestock systems. International Congress on Environmental Modelling and Software Managing Resources of a Limited Planet, Proc. 6th Biennial Meeting (IEMSS2012), Leipzig. 2012.
M. Duru, G. Martin, R. Martin-Clouaire, M. Piquet, M. Sautier. Une méthode innovante de conception participative de systèmes de production agricoles. Symposium PSDR. Les chemins du développement territorial. 2012.
R. Martin-Clouaire, J.-P. Rellier. Dynamic resource allocation in a farm management simulation. Proc. of MODSIM2011, 12-16 December 2011, Perth, AU.
M. Duru , R. Martin-Clouaire. Cognitive tools to support learning about farming system management: a case study in grazing systems. Crop and Pasture Science, 62, 790–802, 2011.
P. Faverdin, X. Chardon, C. Rigolot, C. Baratte, C. Raison, B Piquemal, R. Martin-Clouaire, J.-P. Rellier, A. Le Gall, J.-Y. Dourmad, P. Leterme, J.-M.Paillat, L. Delaby, F. Garcia, J.-L. Peyraud, J.-C. Poupa, T. Morvan, S. Espagnol. Mélodie, un simulateur d'une exploitation d'élevage pour étudier les relations entre conduites des systèmes et risques pour l'environnement. Innovations Agronomiques 12, 109-119. 2011.
A. Ripoche, J.-P. Rellier, R. Martin-Clouaire, N. Paré, A. Biarnès, C. Gary. Modelling adaptive management of intercropping in vineyards to satisfy agronomic and environmental performances under Mediterranean climate. Environmental Modelling & Software, 26(12), 1467-1480, 2011.
G. Martin, R. Martin-Clouaire, J.-P. Rellier, M. Duru. A simulation framework for the design of grassland-based beef-cattle farms. Environmental Modelling & Software, 26(4), 371-385, 2011.
G. Martin, R. Martin-Clouaire, J.-P. Rellier, M. Duru. A Conceptual Model of Grassland-Based Beef Systems. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 2(1), 20-39, 2011.(also in New Technologies for Constructing Complex Agricultural and Environmental Systems (Petraq Papajorgji and François Pinet, eds), IGI Global, pp 100-119, DOI: 10.4018/978-1-4666-0333-2, ISBN13: 9781466603332).
G. Martin, J.-P. Theau, O. Thérond, R. Martin-Clouaire, M. Duru. Diagnosis and Simulation: a suitable combination to support farming systems design. Crop & Pasture Science, 62, 328-336, 2011.
J.-P. Rellier, R. Martin-Clouaire, N. Cialdella, M.-H. Jeuffroy, J.-M. Meynard Modélisation de l’organisation du travail en systèmes de grande culture : méthode et application à l’évaluation ex ante d’innovations variétales de pois. In Le travail en agriculture : son organisation et ses valeurs face à l’innovation (Béguin P; Dedieu B; Sabourin E. eds.), 205-221, L'Harmattan, 2011. ISBN:978-2-296-14012-7
R. Martin-Clouaire, J.-P. Rellier. A generic framework for simulating agricultural production systems. In Modelling nutrient digestion and utilization in farm animals (D. Sauvant, J. van Milgen, P. Faverdin and N. Friggens eds.), Wageningen Academic Publishers, pp. 13-21. 2011. ISBN: 978-90-8686-156-9
X. Chardon, C. Rigolot, C. Baratte, R. Martin-Clouaire, J.-P. Rellier, C. Raison, A. Le Gall, J.-Y. Dourmad, J.-C. Poupa, L. Delaby, T. Morvan, P. Leterme, J.-M. Paillat, S. Espagnol, P. Faverdin. A whole farm-model to simulate the environmental impacts of animal farming systems: MELODIE. In Modelling nutrient digestion and utilization in farm animals (D. Sauvant, J. van Milgen, P. Faverdin and N. Friggens eds.), Wageningen Academic Publishers, pp. 403-411. 2011.
G. Martin, J.‐P. Theau, O. Therond, M.-A. Magne, R. Martin‐Clouaire, M. Duru. Combining plot‐scale indicators and farm‐scale simulation to support the design of novel grassland‐based beef systems. 9th European IFSA Symposium 4‐7 July 2010, Vienna. In Austria Building sustainable rural futures. The added value of systems approaches in times of change and uncertainty Proceedings Edited by: Ika Darnhofer and Michaela Grötzer, 360‐370. 2010.
R. Martin-Clouaire, J.-P. Rellier. Modelling and simulating work practices in agriculture. International Journal of Metadata, Semantics and Ontologies, 4(1-2):42-53, 2009.
N. Cialdella, J.-P. Rellier, R. Martin-Clouaire, M.-H. Jeuffroy, and J.-M. Meynard. Silasol: A model-based assessment of pea (pisum sativum l.) cultivars accounting for crop management practices and farmers’ resources. In Proceedings of Farming Systems Design 2009, Monterey, CA, August 2009.
G. Martin, M. Duru, R. Martin-Clouaire, J.-P. Rellier, and J.-P. Theau. Taking advantage of grassland and animal diversity in managing livestock systems: a simulation study. In Proceedings of Farming Systems Design 2009, August 2009.
G. Martin, L. Hossard, J.-P. Theau, O. Thérond, E. Josien, P. Cruz, J.-P. Rellier, R. Martin-Clouaire, and M. Duru. Characterizing potential flexibility in grassland use. application to the french aubrac area. Agronomy for Sustainable Development, 29(2):381–389, 2009.
A. Ripoche, J P Rellier, R Martin-Clouaire, A Biarnès, N Paré, and C Gary. Modeling dynamically the management of intercropped vineyards to control the grapevine water status. In Proceedings of Farming Systems Design 2009, August 2009.
C. Rigolot, X. Chardon, J.-P. Rellier, R. Martin-Clouaire, J.-Y. Dourmad, A Le Gall, S Espagnol, C Baratte, and P Faverdin. A generic framawork for the modelling of livestock production systems: Melodie. In In Proceedings of Farming Systems Design, Monterey, CA, August 2009.
M. Tchamitchian, R. Martin-Clouaire, B. Jeannequin, J. Lagier, and S Mercier. Serriste: a daily set point determination software for glasshouse tomato production. Computers and Electronics in Agriculture, 50:25-47, 2006.
F. Garcia, F Guerrin, R Martin-Clouaire, and J.-P. Rellier. The human side of agricultural production management - the missing focus in simulation approaches. In Robert M Zerger, Andre; Argent, editor, MODSIM 2005 International Congress on Modelling and Simulation, pages 203-209. Modelling and Simulation Society of Australia and New Zealand, 2005.