{"title":"IEEE Computational Intelligence Society Information","authors":"","doi":"10.1109/TG.2023.3340071","DOIUrl":"https://doi.org/10.1109/TG.2023.3340071","url":null,"abstract":"","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"15 4","pages":"C3-C3"},"PeriodicalIF":2.3,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10361597","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138678652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Call for Papers—IEEE Transactions on Games Special Issue on Computer Vision and Games","authors":"","doi":"10.1109/TG.2023.3338828","DOIUrl":"https://doi.org/10.1109/TG.2023.3338828","url":null,"abstract":"","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"15 4","pages":"683-684"},"PeriodicalIF":2.3,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10361585","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138678689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"RaidEnv: Exploring New Challenges in Automated Content Balancing for Boss Raid Games","authors":"Hyeon-Chang Jeon;In-Chang Baek;Cheong-mok Bae;Taehwa Park;Wonsang You;Taegwan Ha;Hoyoun Jung;Jinha Noh;Seungwon Oh;Kyung-Joong Kim","doi":"10.1109/TG.2023.3335399","DOIUrl":"10.1109/TG.2023.3335399","url":null,"abstract":"The balance of game content significantly impacts the gaming experience. Unbalanced game content diminishes engagement or increases frustration because of repetitive failure. Although game designers intend to adjust the difficulty of game content, this is a repetitive, labor-intensive, and challenging process, especially for commercial-level games with extensive content. To address this issue, the game research community has explored automated game balancing using artificial intelligence (AI) techniques. However, previous studies have focused on limited game content and did not consider the importance of the generalization ability of play-testing agents when encountering content changes. In this study, we propose RaidEnv, a new game simulator that includes diverse and customizable content for the boss raid scenario in the MMORPG games. In addition, we design two benchmarks for the boss raid scenario that can aid in the practical application of game AI. These benchmarks address two open problems in automatic content balancing (ACB), and we introduce two evaluation metrics to provide guidance for AI in ACB. This novel game research platform expands the frontiers of automatic game balancing problems and offers a framework within a realistic game production pipeline. The open-source environment is available at a GitHub repository.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 3","pages":"645-658"},"PeriodicalIF":1.7,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10330736","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Examination of the Hidden Judging Criteria in the Generative Design in Minecraft Competition","authors":"Jean-Baptiste Hervé;Christoph Salge;Henrik Warpefelt","doi":"10.1109/TG.2023.3329763","DOIUrl":"10.1109/TG.2023.3329763","url":null,"abstract":"Game content has long been created using procedural generation. However, many of these systems are currently designed in an ad-hoc manner, and there is a lack of knowledge around the design criteria that lead to generators producing the most successful results. In this study, we conduct a qualitative examination of the comments left by judges for the 2018–2020 \u0000<italic>Generative Design in Minecraft</i>\u0000 competition. Using the abductive thematic analysis, we identify the core design criteria that contribute to a generator that creates “good” content—here defined as interesting or engaging. By performing this study, we have identified that the core design criteria that create an interesting settlement are the usability of the settlement environment, the thematic coherence within the settlement, and an anchoring in real-world simulacra.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 3","pages":"635-644"},"PeriodicalIF":1.7,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135507436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"MDDP: Making Decisions From Different Perspectives in Multiagent Reinforcement Learning","authors":"Wei Li;Ziming Qiu;Shitong Shao;Aiguo Song","doi":"10.1109/TG.2023.3329376","DOIUrl":"10.1109/TG.2023.3329376","url":null,"abstract":"Multiagent reinforcement learning (MARL) has made remarkable progress in recent years. However, in most MARL methods, agents share a policy or value network, which is easy to result in similar behaviors of agents, and thus, limits the flexibility of the method to handle complex tasks. To enhance the diversity of agent behaviors, we propose a novel method, making decisions from different perspectives (MDDP). This method enables agents to switch flexibly between different policy roles and make decisions from different perspectives, which can improve the adaptability of policy learning in complex scenarios. Specifically, in MDDP, we design a new self-attention and gated recurrent unit (GRU)-based dueling architecture network (SG-DAN) to estimate the individual \u0000<inline-formula><tex-math>$Q$</tex-math></inline-formula>\u0000-values. SG-DAN contains two components: 1) the new self-attention-based role-switching network (SAR) and the capable GRU-based state value estimation network (GSE). SAR takes charge of action advantage estimation and GSE is responsible for state value estimation. Experimental results on the challenging \u0000<italic>StarCraft</i>\u0000 II micromanagement benchmark not only verify the modeling reasonability of MDDP but also demonstrate its performance superiority over the related advanced approaches.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 3","pages":"621-634"},"PeriodicalIF":1.7,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134884087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shiwei Zhao;Jiaheng Qi;Zhipeng Hu;Han Yan;Runze Wu;Xudong Shen;Tangjie Lv;Changjie Fan
{"title":"VESPA: A General System for Vision-Based Extrasensory Perception Anticheating in Online FPS Games","authors":"Shiwei Zhao;Jiaheng Qi;Zhipeng Hu;Han Yan;Runze Wu;Xudong Shen;Tangjie Lv;Changjie Fan","doi":"10.1109/TG.2023.3327115","DOIUrl":"10.1109/TG.2023.3327115","url":null,"abstract":"Cheating is widespread in online games, particularly in competitive games, such as \u0000<italic>first-person shooter</i>\u0000 (FPS) games. One of the most common types of cheating is extrasensory perception (ESP), which involves illicitly obtaining visual information to gain an unfair advantage over normal players. To protect the gaming experience of legitimate players and the interests of game companies, there is an urgent need for anticheating applications. In this article, we propose a general system for ESP anticheating in online FPS games, considering the business characteristics and industrial applications. We present a vision-based anticheating framework that incorporates both supervised and unsupervised solutions for comprehensive cheating detection. Based on this framework, we design and deploy a dual-audit human-in-the-loop system for industrial gaming anticheating applications. We evaluate our proposed framework from multiple online and offline perspectives and demonstrate its practical significance with superior performance.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 3","pages":"611-620"},"PeriodicalIF":1.7,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135158252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evaluating the Influence of Imperfect Information in Geister Using DREAM Trained Agents","authors":"Lucien Troillet;Kiminori Matsuzaki","doi":"10.1109/TG.2023.3324737","DOIUrl":"10.1109/TG.2023.3324737","url":null,"abstract":"Imperfect information games (IIGs) are a popular subject in the field of artificial intelligence. In this study, we consider them and propose that they can be classified according to the impact and visualizability of the imperfect information. We use \u0000<italic>Geister</i>\u0000, a Board IIG, to create multiple variant games that we use as an abstraction for IIGs. We then train agents to play each variant using deep regret minimization with advantage baselines and model-free learning, a neural-network variation of counterfactual regret minimization. We observe the performance of our agents and use them to qualitatively assess the characteristics of our IIGs with regards to our proposed terminology.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 3","pages":"598-610"},"PeriodicalIF":1.7,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136371983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gianluca Guglielmo;Michal Klincewicz;Elisabeth Huis in ‘t Veld;Pieter Spronck
{"title":"Tracking Early Differences in Tetris Performance Using Eye Aspect Ratio Extracted Blinks","authors":"Gianluca Guglielmo;Michal Klincewicz;Elisabeth Huis in ‘t Veld;Pieter Spronck","doi":"10.1109/TG.2023.3324511","DOIUrl":"10.1109/TG.2023.3324511","url":null,"abstract":"This study aimed to evaluate if eye blinks can be used to discriminate players with different performance in a session of Nintendo Entertainment System \u0000<italic>Tetris</i>\u0000. To that end, we developed a state-of-the-art method for blink extraction from eye aspect ratio measures, which is robust enough to be used with data collected by a low-grade webcam such as the ones widely available on laptop computers. Our results show a significant decrease in blink rate per minute (blinks/m) during the first minute of playing \u0000<italic>Tetris</i>\u0000. After having defined three groups of proficiency based on in-game performance (novices, intermediates, and experts) we found out that expert players display a significantly lower decrease in blinks/m compared to novices during the first minute of gameplay, which shows that \u0000<italic>Tetris</i>\u0000 players’ proficiency can be detected by looking at eye blinks/m variations during the early phase of a game session. This difference in blinks/m is observed throughout the entire game session, which supports the general conclusion that proficient \u0000<italic>Tetris</i>\u0000 players have a lower decrease in blinks/m, even when playing more difficult levels. Finally, we offer some interpretations of this effect and the relationship that our results may have with the visual cognitive workload experienced during the gameplay.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 3","pages":"735-741"},"PeriodicalIF":1.7,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136302129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Considerations and Concerns of Professional Game Composers Regarding Artificially Intelligent Music Technology","authors":"Kyle Worrall;Tom Collins","doi":"10.1109/TG.2023.3319085","DOIUrl":"10.1109/TG.2023.3319085","url":null,"abstract":"Artificially intelligent music technology (AIMT) is a promising field with great potential for creating innovation in music. However, the considerations and concerns surrounding AI-generated music from the perspective of professional video game composers have yet to be fully explored. In this study, 11 professional video game composers were interviewed to determine how they feel about AIMT and how this informs future research and tool design within the games industry. The interviews were analyzed using a reflexive thematic analysis to identify key themes. The study found that while composers recognize the benefits of music AI, they have complex concerns beyond the obvious concerns of AI infringing on their agency and creativity. There is an inherent clash between the creative ego and music AI, which can make it difficult for composers to embrace this technology. Furthermore, a lack of standard technical knowledge, support, understanding, and trust in music AI is impeding tool use within the industry. These findings have implications for music AI researchers and industry practitioners. By better understanding the concerns and considerations of professional creatives, researchers can design and communicate their tools more effectively to music professionals. Moreover, this study lays the foundation for empirical research into the relationship between professional creatives and emerging AI technology—a topic that is underemphasized in current research.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 3","pages":"586-597"},"PeriodicalIF":1.7,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135699102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Profiling and Identifying Smurfs or Boosters on Dota 2 Using K-Means and IQR","authors":"Ying-Jih Ding;Wun-She Yap;Kok-Chin Khor","doi":"10.1109/TG.2023.3317053","DOIUrl":"10.1109/TG.2023.3317053","url":null,"abstract":"<italic>Dota 2</i>\u0000 is one popular multiplayer online battle arena game, and it holds the grandest e-sports tournament in the world—The International. However, smurfs and boosters are plaguing the game, causing a continuous decline in the player count. Smurfs are skilled players who stomp less experienced players, while boosters are paid to improve players’ rank. At this stage, the developers have brought updates on smurf detection based on players’ complaints, where smurf accounts are likely to be prevented from entering the game. This article proposes a smurf or booster detection among the players by profiling and identifying them based on statistical differences in features. Initially, we created a dataset with player data collected from the OpenDota API. Then, K-means was used to group and profile the players. Subsequently, the interquartile range method was applied to the high-performing players to identify the smurfs or boosters. We then invited three \u0000<italic>Dota 2</i>\u0000 game experts to review the resulting profiles. A 95% accuracy score was achieved using majority voting. The methodology proposed in this article can be implemented in the \u0000<italic>Dota 2</i>\u0000 to detect smurfs or boosters automatically. The findings in this article shall contribute to prolonging the game's life span.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 3","pages":"577-585"},"PeriodicalIF":1.7,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135649570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}