2019 GBDTLRDeepLearningforTurnbasedS

• (Zhang et al., 2019) ⇒ Like Zhang, Hui Pan, Qi Fan, Changqing Ai, and Yanqing Jing. (2019). “GBDT, LR & Deep Learning for Turn-based Strategy Game AI.” In: EasyChair Journal.

Subject Headings: Turn-based Video Game, Video Game Playing Strategy, Cross-Entropy.

Notes

• It focuses on generating fighting strategies (skill-target pair) for StoneAge 2 game.
• It treats the problem as a Recommendation Task.
• It evaluated based on “Win-Rate”.

Cited By

• http://scholar.google.com/scholar?q=%222019%22+GBDT%2C+LR+%26+Deep+Learning+for+Turn-based+Strategy+Game+AI

Quotes

Author Keywords

• Deep learning; Fighting Game; GBDT; logistic regression; machine learning; Recommender System; Stone Age; turn based battle recommendation pipeline; Turn based Game AI.

Abstract

This paper proposes a AI fighting strategies generation approach implemented in the turn-based fighting game StoneAge 2 (SA2) [1]. Our research aim is to develop such AI for choosing the logical skills and targets to the player. The approach trained the logistical regression (LR) model and deep neural networks (DNN) model, individually. And combined both output at inference process. Meanwhile, to transform the features into a higher dimension binary vector without any manual intervention or any prior knowledge, we put all category features into Gradient Boosted Decision Tree (GBDT) before LR component. The main advantage of this procedure is: the approach combines the benefits of LR models (memorization of feature interactions) and DL (generation the unseen feature combination through low-dimensional dense feature) for the AI fighting system. In our experiment, we evaluated our model with some other AI strategies (Reinforcement Learning (RL), GBDT, LR, DNN) to against a robot script. The results shown that the players, participating in the experiment, are capable of using reasonable strategic skills on the different targets. As a consequence, the win rate (versus with the robot script) of our system is higher than the others. Finally, we productionized and evaluated the system on SA 2, a commercial mobile turn-based game.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2019 GBDTLRDeepLearningforTurnbasedS	Like Zhang Hui Pan Qi Fan Changqing Ai Yanqing Jing			GBDT, LR & Deep Learning for Turn-based Strategy Game AI