Automated negotiation in environmental resource management: Review and assessment

Negotiation is an integral part of our daily life and plays an important role in resolving conflicts and facilitating human interactions. Automated negotiation, which aims at capturing the human negotiation process using artificial intelligence and machine learning techniques, is well-established in e-commerce, but its application in environmental resource management remains limited. This is due to the inherent uncertainties and complexity of environmental issues, along with the diversity of stakeholders' perspectives when dealing with these issues. The objective of this paper is to describe the main components of automated negotiation, review and compare machine learning techniques in automated negotiation, and provide a guideline for the selection of suitable methods in the particular context of stakeholders' negotiation over environmental resource issues. We advocate that automated negotiation can facilitate the involvement of stakeholders in the exploration of a plurality of solutions in order to reach a mutually satisfying agreement and contribute to informed decisions in environmental management along with the need for further studies to consolidate the potential of this modeling approach. •The purpose and components of automated negotiation are described.•A comparison of machine learning techniques in automated negotiation is presented.•Their potential for stakeholders' negotiation in environmental studies is evaluated.•Guidelines to select appropriate techniques in environmental studies are proposed.•The study bridges the gap between artificial intelligence and agent-based modeling.