Principle-agent problems comprise a broad context in which two or more parties seek to optimize objectives that are linked and oftentimes conflicting. Modelling these social systems becomes especially complicated when considering asymmetric access to information and uncertainty associated with human behavior as well as system drivers. Integrated modelling frameworks and multi-objective optimization approaches have been widely used to simultaneously optimize conflicting objectives amidst multiple stakeholders while considering various sources of uncertainty. In this session, we seek recent methods and applications of optimization approaches in the context of economic and socio-environmental principle-agent problems. For example, effective targeted agri-environmental policy requires optimization of both policymaker objectives (e.g., minimizing total policy cost, maximizing large-scale environmental benefit) as well as landowner objectives (e.g., maximizing individual profit, maximizing local environmental benefit) to ensure suitable adoption and feasible outcomes. Optimizing integrated economic and environmental objectives using linked models can therefore offer viable policy alternatives as solutions to this principle-agent problem. For this session, submissions focused on applications are encouraged but not limited to agri-environmental and socio-economic policy problems such as related to agricultural management, land use allocations, water rights and use, and adoption of sustainable technology and management. Theoretical or methodological advancements may include but are not limited to the genres of game theory, evolutionary and hybrid algorithms, operations research, hierarchical optimization, evolutionary economics, or agent-based modelling.
Key topics: Optimisation, Principle-Agent models, Integrated modelling, Socio-environmental systems