This document reviews artificial intelligence techniques for modeling systems' sustainability. It discusses different approaches to sustainability modeling including pictorial visualizations, physical models, conceptual models, and standardizing models. It also categorizes quantitative sustainability models into macro-econometric models, computable general equilibrium models, optimization models, system dynamics models, and multi-agent simulation models. The document concludes that influence diagrams can provide an intuitive way to model sustainability and its uncertainties, and that Analytica is a tool that can be used to create influence diagrams and model complex sustainability systems.
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AI Techniques for Modeling Systems' Sustainability
1. Artificial Intelligence Techniques for Modeling Systems' Sustainability: A Review Amin Hosseinian-Far Research Team: Prof. Hamid Jahankhani Mr. Elias Pimenidis Prof. D. C. Wijeyesekera
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