📄 中文摘要
理解考古景观中的移动性、运动和互动对于解读过去的人类行为、运输策略和空间组织至关重要。然而，仅依靠静态考古证据重建这些过程十分困难。该研究提出了一种多智能体建模框架，用于在不均匀地形中模拟考古移动性，整合了真实的地形重建、异质智能体建模和自适应导航策略。所提出的方法结合了全球路径规划与局部动态适应，通过强化学习使智能体能够高效应对动态障碍和互动，而无需昂贵的全球重新规划。该框架为考古研究提供了新的视角，能够更好地理解人类在复杂地形中的移动策略。
基于多智能体的考古移动性不均匀地形模拟
📄 English Summary
Multi-Agent-Based Simulation of Archaeological Mobility in Uneven Landscapes
Understanding mobility, movement, and interaction in archaeological landscapes is crucial for interpreting past human behavior, transport strategies, and spatial organization. However, reconstructing these processes from static archaeological evidence is challenging. A multi-agent-based modeling framework is proposed for simulating archaeological mobility in uneven landscapes, integrating realistic terrain reconstruction, heterogeneous agent modeling, and adaptive navigation strategies. The approach combines global path planning with local dynamic adaptation through reinforcement learning, enabling agents to efficiently respond to dynamic obstacles and interactions without costly global replanning. This framework offers new insights into archaeological research, enhancing the understanding of human mobility strategies in complex terrains.