- author = "Jian Yao and Weiping Wang and Zhifei Li and Yonglin Lei and Qun Li",
- title = "Tactics Exploration Framework based on Genetic Programming",
- journal = "International Journal of Computational Intelligence Systems",
- year = "2017",
- number = "1",
- volume = "10",
- pages = "804--814",
- month = jan,
- keywords = "genetic algorithms, genetic programming, grammar-based genetic programming, tactics exploration framework, behaviour trees, submarine warfare simulation",
-
URL = "
https://download.atlantis-press.com/article/25872437.pdf",
-
DOI = "
doi:10.2991/ijcis.2017.10.1.53",
- abstract = "Engagement-level simulation is a quantitative way to evaluate the effectiveness of weapon systems before construction and acquisition, minimising the risk of investment. Though contractors have built simulation systems with high fidelity models of weapon systems and battlefields, developing competent tactics to give full play to new weapon systems in simulation experiments is labour intensive, as most classical tactics tend to be out of date. In this work, we proposed a tactics exploration framework (TEF) that applied grammar-based genetic programming (GP) to generating and evolving tactics in the engagement level simulation. Tactics are represented with modular behaviour trees (BTs) for compatibility with the genetic operators. Experiments to explore submarine tactics have been conducted to observe and study the exploration process. The experimental results show that the TEF based on GP is efficient to explore tactics in the formalism of BTs.",
-
notes = "journals/ijcisys/Yao0LLL17,
College of Information System and Management National University of Defence Technology 137 Yanwachi, Changsha, Hunan 410073, China",
