A Computer Game Decision Interpretation Method Based on Salient Features
- DOI
- 10.2991/978-94-6463-046-6_4How to use a DOI?
- Keywords
- Explainable Artificial Intelligence; Computer Game; Decision Explanation
- Abstract
Artificial intelligence has greatly improved the efficiency of industry and life, but its algorithmic framework is often a black box, leading to a lack of understanding of how computers give decision results. So, the interpretability of artificial intelligence has been widely concerned in recent years. In this paper, decision interpretation research is done in the field of computer games to try to make humans understand the decision results of game agents. In this paper, three indicators are designed to analyse the game features one by one, which are threatening, relevance and specificity. Finally, all the salient features associated with the decision are given to explain the agent's decisions. Experiments are conducted on two computer games, Surakarta and Mahjong. It is found that salient features not only help humans to understand the behaviours of the agents, but also speed up the decision making of human players in the games. This shows that this paper achieves interpretability of decision making through salient features in the field of computer games.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Haodong Feng AU - Shuqin Li PY - 2022 DA - 2022/12/17 TI - A Computer Game Decision Interpretation Method Based on Salient Features BT - Proceedings of the 2022 2nd International Conference on Computer Technology and Media Convergence Design (CTMCD 2022) PB - Atlantis Press SP - 20 EP - 28 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-046-6_4 DO - 10.2991/978-94-6463-046-6_4 ID - Feng2022 ER -