MASE-EGTI: An agent-based simulator for environmental land change. (January 2022) - Coelho, Cássio Giorgio Couto; Ralha, Célia Ghedini
Abstract: Interacting entities in human society and their roles considering land exploration and occupation are crucial for studying land use/cover change (LUCC) in landscape ecology. For investigation of games in LUCC models, this work presents an agent-based decision model based on evolutionary game theory with three layers of interactive deliberation (individual, peer-to-peer, and social) implemented in MASE-EGTI - Multi-Agent System for Environmental simulation with Evolutionary Game Theory Interactions. The conceptual model details STAIP, an acronym for cellular Space, Time, Agents, Interactions, and Public policy. The theoretical model baseline focus on evolutionary game theory. The experiments use data from MapBiomas Brazilian public geographic database. The results show that agents' peer-to-peer interactions may influence the final land usage and conversion of natural systems. We believe the conducted simulations present insights for LUCC studies that consider space transformation and population interactions. Highlights: We introduce an agent-base decision model with evolutionary game theory. Agents' deliberation model is three-dimensional: individual, peer-to-peer, societal. MASE-EGTI model includes Space, Time, Agents, Interactions, Public policy (STAIP). Experiments use real data from MapBiomas Brazilian public geographic database. Results indicate agents' peer-to-peer interactions influence land usage.