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Résumé. Les démarches de modélisation d’accompagnement (ComMod) et celles du Groupe d’expérimentation et de recherche : développement et actions localisées (Gerdal) facilitent l’émergence de solutions ou de plans d’action négociés au sein de groupes de pairs ou d’arènes d’acteurs hétérogènes, en stimulant les interactions entre leurs participants. Leurs fondements théoriques, éthiques et méthodologiques sont décrits, et leur usage illustré par deux études de cas. Afin d’aider les praticiens à raisonner leur mode d’intervention auprès de collectifs, l’analyse comparée de ces démarches porte sur des points clés de leur accompagnement, tels que la situation initiale, la construction de collectifs pertinents, l’animation des processus, le partage des savoirs et des points de vue, le suivi et l’évaluation des effets, et le renforcement de la capacité à innover collectivement.

This paper is a charter presenting a scientific posture shared by signatories in the use of simulation tools when dealing with complex systems. This posture is based on a cycling approach, in interaction with field processes, including discussion of assumptions and feedbacks on the field process. Confrontation between field and modelling processes has to be permanent because of openness and uncertainty features of these systems. This approach is used with two possible aims: learn on systems or support collective decision processes in these systems, which corresponds to an objective of increasing knowledge either for the scientist or the field actors, always through an interaction between them mediated by an evolutionary model. Both aims lead to different implementations of this companion modelling approach, but each one is side effect of the other one, and has to be taken in account as such. Scientists ready to work in that way and make this posture alive are kindly invited to join.

In this new century, there is an urgent need to integrate and organize knowledge into suitable frameworks to examine essential problems with the people involved in solving them. Recent advances in computer science, particularly distributed artificial intelligence and multi-agent systems (MAS), are creating a strong interest in using this new knowledge and technologies for various applications to better deal with the increasing complexity of our fast-changing world, particularly for studying interactions between societies and their environment. By emphasizing the importance of interactions and points of view, the MAS way of thinking can facilitate high-level interdisciplinary training and collaborative research among scientists working in ecology and social sciences to examine complex problems in the field of integrated natural resource management (INRM). This paper describes how a recent project based on a series of short courses in the field of MAS, social sciences, and INRM at three different universities in Thailand tried to transfer European expertise and research results to an Asian audience of graduate and postgraduate students and young researchers interested in innovative and action-research-oriented interdisciplinary approaches. The course structure, organization, and contents are described and assessed. The course participants are characterized and their opinions are used to evaluate the strengths and weaknesses of this very interdisciplinary training program. The first sustainable outputs and key preliminary lessons learned from this innovative collective learning experience are presented. In conclusion, the authors suggest ways to support the emergence of a regional network of "MAS for INRM" practitioners in Southeast Asia to build on the dynamics begun by this project and serve the need for such interdisciplinary training across Southeast Asia.

Integrated watershed management means a collective management of the land reconciling ecological dynamics and social processes to ensure a sustainable and equitable use of renewable resources. Because different stakeholders have different representations of a local agricultural system, its integrated management can be seen as a collective learning process. New types of models, closely articulated with field work and other participatory tools, can be used to facilitate such collective learning. Particularly, they are useful to elucidate relationships between agent behaviors and interactions, and resource dynamics at different levels of organization. This paper describes and discusses the development and preliminary field testing of such a companion modeling approach, based on the use of multi-agent systems (MAS) associated with role playing games. Companion modeling supports on-farm, interdisciplinary and action-oriented participatory research, to facilitate dialogue, shared learning, negotiation, and collective decisionmaking among multiple stakeholders. The principles of this approach, the characteristics of agentbased models and associated role playing games are explained. Their validation and use with stakeholders to manage renewable natural resources are also presented. The article is illustrated by an on-going case study to improve steep-land management by limiting land degradation in rapidly diversifying and market integrated farming systems of Akha villages in upper northern Thailand. Field work and modeling activities are seen as very complementary, and are closely linked in an iterative way. The collective construction of a common artificial world with stakeholders leads to the emergence of a shared representation of a complex system, and of the concrete problem to be addressed. Later, such a common representation can be used among stakeholders as a coordination and negotiation support tool to identify and to assess scenarios of desirable futures. On the basis of a shared understanding of current systems dynamics, this approach helps to identify acceptable rules for an improved regulation of collective uses of land resources. When a policy of decentralization of natural resource management is implemented, companion modeling can be used to integrate knowledge, to stimulate dialogue and establish adapted coordination mechanisms regarding multiple uses of the land by multiple stakeholders, but also to assess suitable innovations and desirable scenarios of land use changes for the future.

Water is used and managed by stakeholders at different levels for diverse objectives, therefore understanding decision making and supporting coordination is crucial in achieving resilient water management. Companion Modeling (ComMod) is an interactive process facilitated by evolutionary models for knowledge generation and exchange, and for supporting collective decision-making. Role-playing games and computerized multi-agent simulations for focused group debates are complementary tools combined in a ComMod cycle and used at the field workshops. Agent-based modeling is used to understand how different processes in direct competition are coordinated, and to mediate the collective search for acceptable solutions to conflicting parties facilitated through exchanges. This paper compares the process of agent-based modeling applied in eight case studies with diverse natural and socio-economic conditions and different resource management problems in Bhutan, Thailand and Vietnam to show the creative thinking in developing and applying flexible ComMod modeling tools and provide lessons for their use in other situations.

D'importantes réformes sont en cours dans le système semencier thailandais. Dans ce contexte, une série d'ateliers de modélisation participative ont été organisée avec les acteurs du système pour éliciter les besoins et les processus de décision concernant les variétés de riz et l'approvisionnement en semences dans la province d'Ubon Ratchatani. Un modèle conceptuel UML a été produit et partiellement implémenté dans un modèle multi-agent. Le modèle multi-agent permet de simuler sur un pas de temps les besoins et l'allocation des semences des deux principales variétés de riz par les institution publiques, privées ou coopératives au niveau des villages, des districts et des provinces. Un prototype a été présenté et discuté avec les représentants des institutions principales concernées par la réforme en cours. Après cette validation par les usagers, des scénarios possibles ont été proposés pour être simulés avec les modèles multiagents et discutés.

Chapitre 25; National audience