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.

人类社会中的相互作用实体及其在考虑土地勘探和占用方面的作用对于研究景观生态学中的土地利用/覆盖变化 (LUCC) 至关重要。为了研究 LUCC 模型中的博弈，这项工作提出了一个基于进化博弈论的基于代理的决策模型，在 MASE-EGTI - 多代理系统中实现了三层交互式审议（个人、点对点和社会）用于具有进化博弈论交互作用的环境模拟。概念模型详细介绍了 STAIP，它是蜂窝空间、时间、代理、交互和公共政策的首字母缩写词。理论模型基线侧重于进化博弈论。实验使用来自 MapBiomas 巴西公共地理数据库的数据。结果表明，代理人的点对点互动可能会影响自然系统的最终土地使用和转化。我们相信进行的模拟为考虑空间转换和人口相互作用的 LUCC 研究提供了见解。