Ieee Transactions On Games

SCI SCIE

国际简称：IEEE T GAMES 参考译名：IEEE 游戏交易

主要研究方向：Engineering-Electrical and Electronic Engineering 非预警期刊

《IEEE 游戏交易》(Ieee Transactions On Games)是一本由IEEE出版的以Engineering-Electrical and Electronic Engineering为研究特色的国际期刊，发表该领域相关的原创研究文章、评论文章和综述文章，及时报道该领域相关理论、实践和应用学科的最新发现，旨在促进该学科领域科学信息的快速交流。该期刊是一本未开放期刊，近三年没有被列入预警名单。

3区中科院分区
Q2 JCR分区
94 年发文量
3 IF影响因子
未开放 是否OA
2018 创刊年份
4 issues/year 出版周期
English 出版语言

Ieee Transactions On Games (ISSN: 2475-1502) was founded in 2018, and the research direction involved: Engineering-Electrical and Electronic Engineering.

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Ieee Transactions On Games期刊信息

ISSN：2475-1502
出版语言：English
是否OA：未开放
E-ISSN：2475-1510
出版地区：UNITED STATES
是否预警：否
出版商：IEEE
出版周期：4 issues/year
创刊时间：2018
开源占比：0.078
Gold OA文章占比：9.17%
OA被引用占比：
出版国人文章占比：0
出版撤稿占比：
研究类文章占比：94.68%

Ieee Transactions On Games CiteScore评价数据（2026年6月最新版）

CiteScore

SJR

SNIP

CiteScore 指数

5.7

0.551

1.456

学科类别	分区	排名	百分位
大类：Engineering 小类：Electrical and Electronic Engineering	Q2	285 / 1030	72%
大类：Engineering 小类：Control and Systems Engineering	Q2	116 / 390	70%
大类：Engineering 小类：Artificial Intelligence	Q2	194 / 570	66%
大类：Engineering 小类：Software	Q2	181 / 503	64%

名词解释：CiteScore 是衡量期刊所发表文献的平均受引用次数，是在 Scopus 中衡量期刊影响力的另一个指标。当年CiteScore 的计算依据是期刊最近4年（含计算年度）的被引次数除以该期刊近四年发表的文献数。例如，2022年的 CiteScore 计算方法为：2022年的 CiteScore =2019-2022年收到的对2019-2022年发表的文件的引用数量÷2019-2022年发布的文献数量注：文献类型包括：文章、评论、会议论文、书籍章节和数据论文。

Ieee Transactions On Games中科院评价数据

《新锐期刊分区表》（2026年3月发布）

Top期刊	综述期刊	大类学科		小类学科
否	否	计算机科学	3区	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机：人工智能 COMPUTER SCIENCE, SOFTWARE ENGINEERING 计算机：软件工程	3区 3区

Ieee Transactions On Games JCR评价数据

2025-2026年最新版

按JCI指标学科分区	收录子集	分区	排名	百分位
学科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	SCIE	Q3	117 / 210	44.5
学科：COMPUTER SCIENCE, SOFTWARE ENGINEERING	SCIE	Q2	53 / 128	59
学科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	SCIE	Q2	102 / 210	51.67
学科：COMPUTER SCIENCE, SOFTWARE ENGINEERING	SCIE	Q3	66 / 128	48.83

Ieee Transactions On Games历年数据统计

影响因子

中科院分区

Ieee Transactions On Games中国学者发文选摘

1、Relation-Aware Learning for Multitask Multiagent Cooperative Game
Author: Yu, Yang; Yang, Likun; Guo, Zhourui; Ren, Yongjian; Yin, Qiyue; Zhang, Junge; Huang, Kaiqi

Journal: IEEE TRANSACTIONS ON GAMES. 2025; Vol. 17, Issue 2, pp. 322-333. DOI: 10.1109/TG.2024.3436871
2、Learning Individual Potential-Based Rewards in Multiagent Reinforcement Learnin
Author: Yang, Chen; Xu, Pei; Zhang, Junge

Journal: IEEE TRANSACTIONS ON GAMES. 2025; Vol. 17, Issue 2, pp. 334-345. DOI: 10.1109/TG.2024.3450475
3、Efficient Adversarially Guided Actor-Criti
Author: Xu, Mao; Ge, Shuzhi Sam; Zhao, Dongjie; Zhao, Qian

Journal: IEEE TRANSACTIONS ON GAMES. 2025; Vol. 17, Issue 2, pp. 346-359. DOI: 10.1109/TG.2024.3453444
4、Fun as Moderate Divergence: Evaluating Experience-Driven PCG via R
Author: Wang, Ziqi; Li, Yuchen; Du, Haocheng; Liu, Jialin; Yannakakis, Georgios N

Journal: IEEE TRANSACTIONS ON GAMES. 2025; Vol. 17, Issue 2, pp. 360-373. DOI: 10.1109/TG.2024.3456101
5、Research on the Imperfect Information Game of Four-Player Mahjong Based on Mix-PP
Author: Wang, Jia-Yang; Wang, Ming-Yan; Zeng, Wang; Zhong, Zi-An

Journal: IEEE TRANSACTIONS ON GAMES. 2025; Vol. 17, Issue 2, pp. 485-497. DOI: 10.1109/TG.2024.3507107
6、Enhancing AI-Bot Strength and Strategy Diversity in Adversarial Games: A Novel Deep Reinforcement Learning Framewor
Author: Sun, Chenglu; Shen, Shuo; Xue, Deyi; Tao, Wenzhi; Zhou, Zixia

Journal: IEEE TRANSACTIONS ON GAMES. 2025; Vol. 17, Issue 2, pp. 522-535. DOI: 10.1109/TG.2024.3520970
7、Biosignal Contrastive Representation Learning for Emotion Recognition of Game User
Author: Li, Rongyang; Ding, Jianguo; Ning, Huansheng

Journal: IEEE TRANSACTIONS ON GAMES. 2025; Vol. 17, Issue 2, pp. 308-321. DOI: 10.1109/TG.2024.3435339
8、CuDA2: An Approach for Incorporating Traitor Agents Into Cooperative Multiagent System
Author: Chen, Zhen; Liao, Yong; Zhao, Youpeng; Dai, Zipeng; Zhao, Jian

Journal: IEEE TRANSACTIONS ON GAMES. 2025; Vol. 17, Issue 2, pp. 397-407. DOI: 10.1109/TG.2024.3485726