Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference最新文献_第5页

Assessing the Effects of Interacting with MAP-Elites 评估与地图精英互动的影响

Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-10-04 DOI: 10.1609/aiide.v17i1.18899

Alberto Alvarez, J. Font, S. Dahlskog, J. Togelius

引用次数: 5

Search-Based Exploration and Diagnosis of TOAD-GAN 基于搜索的TOAD-GAN探索与诊断

Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-10-04 DOI: 10.1609/aiide.v17i1.18901

Maria Edwards, Ming-Xiu Jiang, J. Togelius

{"title":"Search-Based Exploration and Diagnosis of TOAD-GAN","authors":"Maria Edwards, Ming-Xiu Jiang, J. Togelius","doi":"10.1609/aiide.v17i1.18901","DOIUrl":"https://doi.org/10.1609/aiide.v17i1.18901","url":null,"abstract":"Generative Adversarial Networks (GANs) have been used with great success to generate images. They have also been applied to the task of Procedural Content Generation (PCG) in games, particularly for level generation, with various approaches taken to solving the problem of training data. One of those approaches, TOAD-GAN (Token-Based One-Shot Arbitrary Dimension Generative Adversarial Network) (Awiszus, Schubert, and Rosenhahn 2020), can generate levels based on a single training example and has been able to closely reproduce token patterns found in the training sample. While TOAD-GAN is an impressive achievement, questions remain about what exactly it has learned. Can the generator be made to produce levels that are substantially different from the level it has been trained on? Can it reproduce specific level segments? How different are the generated levels? We investigate these questions and others by using the CMA-ES algorithm for Latent Space Evolution. To make the search space feasible, we use a random projection in latent space. We propose the investigation undertaken here as a paradigm for studies into what machine-learned generators have actually learned, and also as a test of a new method for projecting from a smaller search space to a larger latent space.","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"158 1","pages":"140-147"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79978443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reinforcement Learning Methods to Evaluate the Impact of AI Changes in Game Design 评估游戏设计中AI变化影响的强化学习方法

Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-10-04 DOI: 10.1609/aiide.v17i1.18885

P. Gutiérrez-Sánchez, M. A. Gómez-Martín, P. González-Calero, P. P. Gómez-Martín

{"title":"Reinforcement Learning Methods to Evaluate the Impact of AI Changes in Game Design","authors":"P. Gutiérrez-Sánchez, M. A. Gómez-Martín, P. González-Calero, P. P. Gómez-Martín","doi":"10.1609/aiide.v17i1.18885","DOIUrl":"https://doi.org/10.1609/aiide.v17i1.18885","url":null,"abstract":"Game development has become a long process that requires many professionals working on a project during several months or years. With this scenario the re-utilization of resources is crucial not only to alleviate the process but also to bring coherence into the final product. In this paper we focus on the reuse of NPCs and the problems it brings about. In particular it is common to have different breeds (or personalities) of NPCs that are placed on different levels on the game. The problem arises when their behaviors are fine-tuned to accommodate a specific level needs without taking into consideration that this change may alter their performance on previous already-tested levels. The paper presents the application of reinforcement learning together with behavior trees to automatically test if modifications to the AIs of a stealth game have an impact on the user experience. Our experiments reveal that this approach provides a way of diagnosing alterations in level gameplay that correspond to the effects observed by human testers.","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"13 1","pages":"10-17"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82376197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Generating Tailored Advice in Video Games through Play-Style Identification and Player Modelling 通过游戏风格识别和玩家建模在电子游戏中生成定制建议

Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-10-04 DOI: 10.1609/aiide.v17i1.18913

Branden Ingram

{"title":"Generating Tailored Advice in Video Games through Play-Style Identification and Player Modelling","authors":"Branden Ingram","doi":"10.1609/aiide.v17i1.18913","DOIUrl":"https://doi.org/10.1609/aiide.v17i1.18913","url":null,"abstract":"Recent advances in fields such as reinforcement learning have enabled the development of systems that are able to achieve super-human performance on a number of domains, specifically in complex games such as Go and StarCraft. Based on these successes, it is reasonable to ask if these learned behaviours could be utilised to improve the performance of humans on the same tasks. However, the types of models used in these systems are typically not easily understandable, and can not be directly used to improve the performance of a human. My research looks to address these difficulties by developing a system that can provide advice tailored to a player's style in a video game setting. This system would be particularly useful for improving tutorial systems that quickly become redundant lacking any personalization. I have already developed an unsupervised approach to identifying different play-styles present in a video game. I look to use this knowledge to train agents which can demonstrate optimal behaviour for each style. It is hoped that this information can be utilised to generate useful advice based on the differences between the current performance of a player and the corresponding expert agent in their style.","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"25 1","pages":"228-231"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89362803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing Profit by Mitigating Recurrent Churn Labeling Issues: Analysis from the Game Domain 通过减少反复流失的标签问题来优化利润:来自游戏领域的分析

Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-10-04 DOI: 10.1609/aiide.v17i1.18887

João Felipe Humenhuk, L. Kummer, E. Paraiso

{"title":"Optimizing Profit by Mitigating Recurrent Churn Labeling Issues: Analysis from the Game Domain","authors":"João Felipe Humenhuk, L. Kummer, E. Paraiso","doi":"10.1609/aiide.v17i1.18887","DOIUrl":"https://doi.org/10.1609/aiide.v17i1.18887","url":null,"abstract":"Churn can be interpreted as customer defection and can be considered one of the most critical challenges in the Game Analytics domain because of its impact on the game industry's profit. When predicting churn, the first step is defining what is considered churn, which can change depending on the players' behaviors and approaches. This work studied related works and revealed two recurrent issues in the labeling process: limitations on the adopted labeling approaches (1) and the static definition of churn (2). To mitigate the first issue, an individualized labeling approach was deployed. To address the second one, a novel evaluation method, based on the impact of a change in the churn definition, was proposed. This method allowed the proposition of two new labeling approaches, which were included in the analysis. By comparing the labeling approaches in two games using a profit perspective, it was identified that the new ones present statistically significant benefits compared to the traditional ones. Regarding the evaluation method, its usage can justify when the redefinition of churn and the classifier's retraining should happen to improve profit. The results are valuable for the game context, potentially extended to other contexts by delivering more reliable labels and more validated classification performance.","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"12 1","pages":"26-33"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86918643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

MappyLand: Fast, Accurate Mapping for Console Games MappyLand:快速，准确的主机游戏地图

Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-10-04 DOI: 10.1609/aiide.v17i1.18892

J. Osborn, A. Summerville, Nathan Dailey, Soksamnang Lim

引用次数: 3

Automated Personalized Exposure Therapy Based on Physiological Measures Using Experience-Driven Procedural Content Generation 基于体验驱动程序内容生成的生理测量的自动个性化暴露治疗

Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-10-04 DOI: 10.1609/aiide.v17i1.18914

Athar Mahmoudi-Nejad

引用次数: 2

A Case Study in Learning in Metagames: Super Smash Bros. Melee 学习元游戏的案例研究:《Super Smash Bros. Melee

Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-10-04 DOI: 10.1609/aiide.v17i1.18884

Julien Codsi, A. Vetta

引用次数: 0

A Force Dynamic Model of Narrative Agents 叙事主体的力动态模型

Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-10-04 DOI: 10.1609/aiide.v17i1.18890

Quinn Kybartas, Clark Verbrugge, Jonathan Lessard

引用次数: 0

TAG: Terraforming Mars 改造火星

Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference Pub Date : 2021-10-04 DOI: 10.1609/aiide.v17i1.18902

Raluca D. Gaina, James Goodman, Diego Perez-Liebana

引用次数: 4