An Empirical Comparison of Search Approaches for Moving Agents

作者：Arica Nafiz^*; Mut Aysegul; Yorukcu Alper; Demir Kadir Alpaslan

来源：Computational Intelligence, 2017, 33(3): 368-400.

DOI：10.1111/coin.12092

• path planning
• incremental search
• real-time search
• moving agents
• partially observable environment

This study empirically compares existing search approaches used for path planning of moving agents, namely, incremental and real-time search approaches. The comparisons are performed in both stationary and moving target search problems separately. In each problem domain, well-known representatives of both approaches are evaluated in partially observable environments where the agent senses a limited area based on its sensor range. In addition to the available algorithms, we propose two algorithms to be used in each problem. The simulations conducted on random grid and maze structures show that the algorithms behave differently and have advantages over each other especially as the sensor range varies. Therefore, the proposed study enables the agent to determine the most appropriate algorithm depending on its priorities and sensor range.

• 出版日期2017-8
• 单位中国人民解放军海军大连舰艇学院