The underlying decision theory of forest management changed from decisions made by the forest manager, a single stakeholder, to a decision-making process, which involves a variety of stakeholders with different goals. From concept to implementation, forest professionals are in trouble because, despite the potential of technological progress and the development of tools to support decision-making, tools to facilitate multi-stakeholder decisions are lacking. This paper proposes a framework to link social, economic, and biophysical dynamics using multi-agent simulation to explore scenarios of collaboration for forest plantation management. The modeling is based on decision theories. This framework uses the concept of a value-added chain as a model of alliances. The added-value breakdown analysis is a tool, which is used at the forest-plot level as a means of anticipating benefit sharing among the stakeholders before they decide to harvest; this also highlights the added-value variation from plot to plot. The framework can also take into account noneconomic-based relationships. Each stakeholder has explicit communication capacities, behaviors, and rationales, and forest management emerges from their interactions. The purpose of this modeling is to produce shared knowledge about dynamics to facilitate coordination among stakeholders; it is a learning tool about forest management. Our main hypothesis is that stakeholders, by creating a virtual world with researchers, will learn about the effects that their own decisions might have on themselves, others, and the environment. In the case of Sabah, we are at the stage of the first loop of learning, and scenarios need to be further tested with the stakeholders themselves. This forest plantation simulation suggests that the development of sawmills adapted to plantation wood might offer a promising pathway for increasing added value and the benefits of many stakeholders, including local communities.