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Full-Text Articles in Computer Engineering
Empirical Agent-Based Modelling Of Everyday ProEnvironmental Behaviours At Work, Gary Polhill, Tony Craig, Amparo Alonso-Betanzos, Noelia Sanchez-Maroño, Óscar Fontenla-Romero, Adina Dumitru, Mirilia Bonnes, Marini Bonaiuto, Giuseppe Carrus, Ferdinando Fornara, Fridanna Maricchiolo, Linda Steg, Angela Ruepert, Kees Kaizer, Ricardo García-Mira
Empirical Agent-Based Modelling Of Everyday ProEnvironmental Behaviours At Work, Gary Polhill, Tony Craig, Amparo Alonso-Betanzos, Noelia Sanchez-Maroño, Óscar Fontenla-Romero, Adina Dumitru, Mirilia Bonnes, Marini Bonaiuto, Giuseppe Carrus, Ferdinando Fornara, Fridanna Maricchiolo, Linda Steg, Angela Ruepert, Kees Kaizer, Ricardo García-Mira
International Congress on Environmental Modelling and Software
We report on agent-based modelling work in the LOCAW project (Low Carbon at Work: Modelling Agents and Organisations to Achieve Transition to a Low Carbon Europe). The project explored the effectiveness of various backcasting scenarios conducted with case study organisations in bringing about pro-environmental change in the workforce in the domains of transport, energy use and waste. The model used qualitative representations of workspaces in formalising each scenario, and decision trees learned from questionnaire responses to represent decision-making. We describe the process by which the decision trees were constructed, noting that the use of decision trees in agent-based models requires …
Multiscale Spatial Sensitivity Analysis For Agent-Based Modelling Of Coupled Landscape And Aquatic Systems, Arika Ligmann-Zielinska, Wei Liu, Daniel B. Kramer, Kendra Spence Cheruvelil, Patricia A. Soranno, Piotr Jankowski, Seda Salap
Multiscale Spatial Sensitivity Analysis For Agent-Based Modelling Of Coupled Landscape And Aquatic Systems, Arika Ligmann-Zielinska, Wei Liu, Daniel B. Kramer, Kendra Spence Cheruvelil, Patricia A. Soranno, Piotr Jankowski, Seda Salap
International Congress on Environmental Modelling and Software
Models of coupled landscape and aquatic systems (CLAS) are prone to input uncertainties that vary over space. To address this challenge, we employ a comprehensive model evaluation that: [1] quantifies the variability of model results (uncertainty analysis), and [2] decomposes this variability based on the relative contribution of inputs to identify major drivers in the model (sensitivity analysis). Our study simulates how agricultural land conversion from active to fallow lands reduces nutrient loading to lakes. We employ an agent-based model of farmer decision making coupled with a spatially-explicit biophysical lake model. A number of model inputs are uncertain including: variables …