IEEE Transactions on Games最新文献_第8页

GAILPG: Multiagent Policy Gradient With Generative Adversarial Imitation Learning GAILPG：多代理策略梯度与生成式对抗模仿学习

IF 1.7 4区计算机科学

IEEE Transactions on Games Pub Date : 2024-03-14 DOI: 10.1109/TG.2024.3375515

Wei Li;Shiyi Huang;Ziming Qiu;Aiguo Song

{"title":"GAILPG: Multiagent Policy Gradient With Generative Adversarial Imitation Learning","authors":"Wei Li;Shiyi Huang;Ziming Qiu;Aiguo Song","doi":"10.1109/TG.2024.3375515","DOIUrl":"10.1109/TG.2024.3375515","url":null,"abstract":"In reinforcement learning, the agents need to sufficiently explore the environment and efficiently exploit the existing experiences before finding the solution to the tasks, particularly in cooperative multiagent scenarios where the state and action spaces grow exponentially with the number of agents. Hence, enhancing the exploration ability of agents and improving the utilization efficiency of experiences are two critical issues in cooperative multiagent reinforcement learning. We propose a novel method called generative adversarial imitation learning policy gradients (GAILPG). The contributions of GAILPG are as follows: first, we integrate generative adversarial self-imitation learning into the multiagent actor–critic framework to improve the utilization efficiency of experiences, thus further assisting the policy training; second, we design a new curiosity module to enhance the exploration ability of the agents. Experimental results on the <italic>StarCraft II micromanagement benchmark demonstrate that GAILPG surpasses state-of-the-art policy-based methods and is even on par with the value-based methods and the ablation experiments validate the reasonability of the discriminator module and the curiosity module encapsulated in our method.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 1","pages":"62-75"},"PeriodicalIF":1.7,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140146697","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}

引用次数: 0

The Iceberg Profile Does Not Influence the Performance of Elite League of Legends Players, but Changes With the Events of the Game 冰山轮廓不会影响《英雄联盟》精英玩家的表现，但会随着游戏事件的发生而改变

IF 1.7 4区计算机科学

IEEE Transactions on Games Pub Date : 2024-03-14 DOI: 10.1109/TG.2024.3377604

Adrián Mateo-Orcajada;Lucía Abenza-Cano;Juan Pablo Rey-López;Raquel Vaquero-Cristóbal

{"title":"The Iceberg Profile Does Not Influence the Performance of Elite League of Legends Players, but Changes With the Events of the Game","authors":"Adrián Mateo-Orcajada;Lucía Abenza-Cano;Juan Pablo Rey-López;Raquel Vaquero-Cristóbal","doi":"10.1109/TG.2024.3377604","DOIUrl":"10.1109/TG.2024.3377604","url":null,"abstract":"Little is known about the interactions between the iceberg profile, which is characterized by high vigor scores, as opposed to low scores in tension, depression, anger, fatigue, and confusion, and performance in <italic>League of Legends (LOL). For these reasons, the objectives of the present research were to analyze whether the performance was influenced by the presence of the iceberg profile before the start of the game and to determine the changes produced in the iceberg profile of esports players as a function of the final outcome of the game, the players' performance during the game, and pregame anxiety and self-confidence. The participants were players in a professional LOL esports team during a SuperLiga Orange spring split. The profile of mood states and competitive state anxiety inventory-2 questionnaires were used. Performance was assessed using in-game variables, such as game result, favorable and unfavorable plays, and kills/deaths/assists ratio. The results showed that no changes were found in the performance of the players according to the pregame iceberg profile. Changes were found in the pre- and postgame iceberg profile, according to the final outcome of the game, and the favorable and unfavorable plays. Furthermore, the psychological variables cognitive and somatic anxiety, and self-confidence, had a relationship with the presence or absence of the iceberg profile. To conclude, the iceberg profile does not seem to influence the performance of esports players, although it is modified by events that occur during the game.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 1","pages":"76-87"},"PeriodicalIF":1.7,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140146973","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}

引用次数: 0

The First ChatGPT4PCG Competition 第一届 ChatGPT4PCG 竞赛

IF 1.7 4区计算机科学

IEEE Transactions on Games Pub Date : 2024-03-12 DOI: 10.1109/TG.2024.3376429

Febri Abdullah;Pittawat Taveekitworachai;Mury F. Dewantoro;Ruck Thawonmas;Julian Togelius;Jochen Renz

{"title":"The First ChatGPT4PCG Competition","authors":"Febri Abdullah;Pittawat Taveekitworachai;Mury F. Dewantoro;Ruck Thawonmas;Julian Togelius;Jochen Renz","doi":"10.1109/TG.2024.3376429","DOIUrl":"10.1109/TG.2024.3376429","url":null,"abstract":"This article summarizes the first ChatGPT4PCG competition held at the 2023 IEEE Conference on Games. The goal of the competition is to explore emergent abilities of publicly available large language models (LLMs) in performing complex tasks related to procedural content generation, specifically physics-based level generation for \u0000<italic>Angry Birds\u0000-like games. Participants are tasked with submitting their prompts for ChatGPT to generate \u0000<italic>Angry Birds\u0000-like game structures that resemble English uppercase characters. A structure is a collection of stacked game objects comprising a part of an entire \u0000<italic>Angry Birds\u0000-like level. A prompt is an input for LLMs, including ChatGPT. Two evaluation metrics, i.e., stability and similarity, are used to evaluate the submitted prompts. Stability measures the sturdiness of a structure to withstand in-game gravity, while similarity measures a structure's resemblance to the target character. With such evaluation, participants are challenged to produce not only character-like but also stable structures by utilizing prompt engineering techniques. Finally, the competition's results are discussed to provide valuable insights for future studies and competitions.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 4","pages":"971-980"},"PeriodicalIF":1.7,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140115320","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}

引用次数: 0

A Hetero-Relation Transformer Network for Multiagent Reinforcement Learning 用于多代理强化学习的异关系变压器网络

IF 1.7 4区计算机科学

IEEE Transactions on Games Pub Date : 2024-03-10 DOI: 10.1109/TG.2024.3399167

Junho Park;Sukmin Yoon;Yong-Duk Kim

{"title":"A Hetero-Relation Transformer Network for Multiagent Reinforcement Learning","authors":"Junho Park;Sukmin Yoon;Yong-Duk Kim","doi":"10.1109/TG.2024.3399167","DOIUrl":"10.1109/TG.2024.3399167","url":null,"abstract":"Recently, considerable research has been focused on multiagent reinforcement learning to effectively account for each agent's relations. However, most research has focused on homogeneous multiagent systems with the same type of agents, which has limited application to heterogeneous multiagent systems. The demand for heterogeneous systems has considerably increased not only in games but also in the real world. Therefore, a technique that can properly consider relations in heterogeneous systems is required. In this article, we propose a novel transformer network called <italic>HRformer, which is based on heterogeneous graph networks that can reflect the heterogeneity and relations among agents. To this end, we design an effective linear encoding method for the transformer to receive input of the various and unique characteristics of the agents and introduce a novel encoding method to model the relations among them. Experiments are conducted in the <italic>StarCraft multiagent challenge environment, the most famous heterogeneous multiagent simulation, to demonstrate the superior performance of the proposed method compared with the other existing methods in various heterogeneous scenarios. The proposed method in our simulation shows a high win rate and fast convergence speed, proving the superiority of the proposed method considering the heterogeneity of the multiagent system.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 1","pages":"138-147"},"PeriodicalIF":1.7,"publicationDate":"2024-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140930216","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}

引用次数: 0

Simulation-Driven Balancing of Competitive Game Levels With Reinforcement Learning 利用强化学习实现竞技游戏关卡的模拟驱动平衡

IF 1.7 4区计算机科学

IEEE Transactions on Games Pub Date : 2024-03-10 DOI: 10.1109/TG.2024.3399536

Florian Rupp;Manuel Eberhardinger;Kai Eckert

{"title":"Simulation-Driven Balancing of Competitive Game Levels With Reinforcement Learning","authors":"Florian Rupp;Manuel Eberhardinger;Kai Eckert","doi":"10.1109/TG.2024.3399536","DOIUrl":"10.1109/TG.2024.3399536","url":null,"abstract":"The balancing process for game levels in competitive two-player contexts involves a lot of manual work and testing, particularly for nonsymmetrical game levels. In this work, we frame game balancing as a procedural content generation task and propose an architecture for automatically balancing of tile-based levels within the procedural content generation via reinforcement learning framework (PCGRL) framework. Our architecture is divided into three parts: first, a level generator, second, a balancing agent, and third, a reward modeling simulation. Through repeated simulations, the balancing agent receives rewards for adjusting the level toward a given balancing objective, such as equal win rates for all players. To this end, we propose new swap-based representations to improve the robustness of playability, thereby enabling agents to balance game levels more effectively and quickly compared to traditional PCGRL. By analyzing the agent's swapping behavior, we can infer which tile types have the most impact on the balance. We validate our approach in the neural massively multiplayer online environment in a competitive two-player scenario. In this article, we present improved results, explore the applicability of the method to various forms of balancing beyond equal balancing, compare the performance to another search-based approach, and discuss the application of existing fairness metrics to game balancing.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 4","pages":"903-913"},"PeriodicalIF":1.7,"publicationDate":"2024-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140929989","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}

引用次数: 0

Towards Real-time G-buffer-Guided Style Transfer in Computer Games 在电脑游戏中实现实时 G-buffer 引导的风格转移

IF 2.3 4区计算机科学

IEEE Transactions on Games Pub Date : 2024-03-04 DOI: 10.1109/tg.2024.3372829

Eleftherios Ioannou, Steve Maddock

引用次数: 0

Predicting Wargame Outcomes and Evaluating Player Performance From an Integrated Strategic and Operational Perspective 从战略和行动的综合视角预测战争游戏结果和评估玩家表现

IF 1.7 4区计算机科学

IEEE Transactions on Games Pub Date : 2024-02-23 DOI: 10.1109/TG.2024.3369330

Yusheng Sun;Yuxiang Sun;Jiahui Yu;Yuanbai Li;Xianzhong Zhou

{"title":"Predicting Wargame Outcomes and Evaluating Player Performance From an Integrated Strategic and Operational Perspective","authors":"Yusheng Sun;Yuxiang Sun;Jiahui Yu;Yuanbai Li;Xianzhong Zhou","doi":"10.1109/TG.2024.3369330","DOIUrl":"10.1109/TG.2024.3369330","url":null,"abstract":"Wargame has emerged as a preferred instrument for simulating combat decision-making. However, the protracted duration of wargame matches and the extensive volume of intricate data records have led to a scarcity of comprehensive datasets containing explicit information. Consequently, a substantial reservoir of detailed match data remains underutilized, hindering research endeavors in data mining and the analysis of player behavior within the realm of wargaming. To address these formidable challenges, this article employs machine learning methodologies to predict the outcome of wargame matches. Initially, we conducted data preprocessing on 335 wargame match replays, extracting and generating features from both macro- and microperspectives, thereby capturing player strategies and operational nuances. This meticulous process culminated in the formation of a comprehensive player behavioral feature dataset. Subsequently, we harnessed six distinct machine learning models to prognosticate match results in the domain of wargaming using this dataset, achieving a peak prediction accuracy of 96.11%. The primary emphasis lies in the identification of prevalent determinants contributing to player triumphs in wargaming. To this end, we conducted an attribution analysis to ascertain the significance of diverse macro- and microfeatures. Guided by the importance of these features, we propose a method for evaluating player performance. This methodology can be instrumental in scrutinizing disparate player wargaming styles, dissecting customary strategic behaviors that lead to player victories, and assisting wargame designers in crafting AI agents capable of adapting to a spectrum of human player behaviors. Consequently, this study offers substantial insights for the advancement of research in the realm of human–AI hybrid gameplay.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 4","pages":"770-782"},"PeriodicalIF":1.7,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953664","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}

引用次数: 0

Puzzle-Level Generation With Simple-Tiled and Graph-Based Wave Function Collapse Algorithms 用简单平铺算法和基于图形的波函数折叠算法生成谜题级别

IF 1.7 4区计算机科学

IEEE Transactions on Games Pub Date : 2024-02-21 DOI: 10.1109/TG.2024.3368017

Hwanhee Kim;Beomjoo Seo;Shinjin Kang

引用次数: 0

Cultural Insights in Souls-Like Games: Analyzing Player Behaviors, Perspectives, and Emotions Across a Multicultural Context 类灵魂游戏中的文化洞察：分析多元文化背景下玩家的行为、观点和情感

IF 1.7 4区计算机科学

IEEE Transactions on Games Pub Date : 2024-02-15 DOI: 10.1109/TG.2024.3366239

Sicheng Pan;Gary J. W. Xu;Kun Guo;Seop Hyeong Park;Hongliang Ding

{"title":"Cultural Insights in Souls-Like Games: Analyzing Player Behaviors, Perspectives, and Emotions Across a Multicultural Context","authors":"Sicheng Pan;Gary J. W. Xu;Kun Guo;Seop Hyeong Park;Hongliang Ding","doi":"10.1109/TG.2024.3366239","DOIUrl":"10.1109/TG.2024.3366239","url":null,"abstract":"<italic>Souls-like\u0000 games are one of the most popular and emerging genres in the contemporary gaming world. This study compared the behavioral characteristics, perspectives, and emotional expressions of players in \u0000<italic>Souls-like\u0000 games from different cultural backgrounds, specifically examining the distinctions and commonalities among them. Natural language processing techniques were employed to analyze English, Chinese, and Russian reviews of 17 \u0000<italic>Souls-like\u0000 games to investigate players' gaming experiences, including gameplay behaviors, game evaluations, and emotional experiences. The findings revealed significant disparities among players from different cultures in all three aspects of their engagement with \u0000<italic>Souls-like\u0000 games. Specifically, these players exhibited significant culture-related variations in their behavioral characteristics toward \u0000<italic>Souls-like\u0000 games. In terms of perspectives, English-speaking players tended to focus more on game optimization, whereas Chinese and Russian players paid greater attention to game combat design. Regarding emotional expressions, Chinese players were more prone to exhibit emotions of anger and disgust, while English and Russian players displayed a more neutral emotional stance. These cultural insights provide valuable information for game developers to better meet the needs and expectations of players from different cultural backgrounds. This study not only broadens our understanding of player behaviors and cultural influences but also lends robust support to cross-cultural gaming research.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 4","pages":"758-769"},"PeriodicalIF":1.7,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953760","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}

引用次数: 0

GamiDOC: The Importance of Designing Gamification in a Proper Way GamiDOC：正确设计游戏化的重要性

IF 1.7 4区计算机科学

IEEE Transactions on Games Pub Date : 2024-02-08 DOI: 10.1109/TG.2024.3364061

Simone Bassanelli;Antonio Bucchiarone;Federica Gini

{"title":"GamiDOC: The Importance of Designing Gamification in a Proper Way","authors":"Simone Bassanelli;Antonio Bucchiarone;Federica Gini","doi":"10.1109/TG.2024.3364061","DOIUrl":"10.1109/TG.2024.3364061","url":null,"abstract":"Gamification, commonly described as the use of game design elements in nongame contexts, is frequently adopted to enhance users' motivation, engagement, and happiness while supporting them in reaching different objectives, related to learning activities and behavioral changes. Despite being a widely used approach, several studies show that the final outcomes following gamification use are not always positive. To face this problem, we developed a tool called GamiDOC composed of different features aimed at facing the existing problems in the gameful systems design process and, at the same time, guiding designers and practitioners in the design and evaluation of gamified solutions. In this article, we present the elements that make gameful systems design a challenging process, the state of the art in gamification design, and the issues that are still open in the design of gameful systems. Finally, we provide a detailed description of GamiDOC and why the tool stands as a valuable solution to guide users across all the stages of gameful systems design, development, and evaluation. Finally, we present a usability evaluation of GamiDOC and a use-case scenario.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 1","pages":"13-31"},"PeriodicalIF":1.7,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953754","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}

引用次数: 0