Tactics Exploration Framework based on Genetic Programming

DOI

10.2991/ijcis.2017.10.1.53How to use a DOI?

Keywords

tactics exploration framework; grammar-based genetic programming; behavior trees; submarine warfare simulation

Abstract

Engagement-level simulation is a quantitative way to evaluate the effectiveness of weapon systems before construction and acquisition, minimizing 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give full play to new weapon systems in simulation experiments is labor intensive, as most classical tactics tend to be out of date.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 behavior 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.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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TY  - JOUR
AU  - Jian Yao
AU  - Weiping Wang
AU  - Zhifei Li
AU  - Yonglin Lei
AU  - Qun Li
PY  - 2017
DA  - 2017/03/07
TI  - Tactics Exploration Framework based on Genetic Programming
JO  - International Journal of Computational Intelligence Systems
SP  - 804
EP  - 814
VL  - 10
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2017.10.1.53
DO  - 10.2991/ijcis.2017.10.1.53
ID  - Yao2017
ER  -