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检索条件"任意字段=3rd European Conference on Games Based Learning"

共 1043 条记录，以下是1-10 订阅

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Optimizing NPC Behavior in Video games Using Unity ML-Agents: A Reinforcement learning-based Approach 3

Optimizing NPC Behavior in Video Games Using Unity ML-Agents...

引用

3rd International conference on Disruptive Technologies, ICDT 2025

作者： Maurya, Sudhanshu Kotiyal, Arnav Prusty, Pankaj Shelke, Nilesh Bhattacherjee, Abhishek Sarkar, Tiyas School Of Computer Science and Engineering Nagpur Campus Pune India Graphic Era Deemed to be University Department of Computer Science and Engineering Dehradun India Siksha O Anusandhan Deemed to be University Department of Computer Science and Engineering Bhubaneswar India School of Computer Science and Engineering Lovely Professional University Phagwara India

ISBN: (纸本)9798331519582

The development of video games is now being influenced by machine learning (ML), which is changing the industry with every passing day. The focus of this research is on how video games can be made better through ML in game development, particularly how NPCs behave in the game. Game companies can boost the immerse feeling in video games by utilizing reinforcement learning in developing sophisticated NPCs. Those who play modern video games know that they are more realistic than what they used to be, and this is courtesy of ML. The toolkit Unity ML-Agents enables more straightforward ML implementations in the Unity game engine, giving game makers the ability to create complex AI features without having to have deep knowledge of machine learning. This paper seeks to analyze how ML can transform the experience of humans when playing games by enhancing the NPCs and through interactivity. The future of video games is bright, especially considering new advancements in technology like ML. © 2025 IEEE.

关键词： Reinforcement learning

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Software Design Decisions for Greener Machine learning-based Systems 24

Software Design Decisions for Greener Machine Learning-based...

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IEEE/ACM 3rd International conference on AI Engineering - Software Engineering for AI (CAIN)

作者： del Rey, Santiago Univ Politecn Cataluna Barcelona Spain

ISBN: (纸本)9798400705915

The widespread integration of Machine learning (ML) in software systems has brought forth unprecedented advancements, yet the surge in energy consumption raises ecological concerns. This research addresses the environmental impact of ML development, focusing on the energy implications of design decisions in ML-based systems. This thesis aims to offer insights into the energy consumption patterns influenced by deployment architecture and training environment. Different case studies on ML-based systems will be conducted to validate and demonstrate the implications of these design choices. The expected outcomes encompass actionable insights, validated through rigorous evaluations, and the development of an energy prediction tool for ML-based system development, to help in the decision-making process. This work contributes to the broader field of Green AI by addressing a critical gap and guiding the transition towards a more sustainable AI landscape.

关键词： Green AI energy efficiency software engineering sustainable computing

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What Matters to Patients: Community-Engaged Design for Healthcare-Related Serious games 18

What Matters to Patients: Community-Engaged Design for Healt...

引用

18th european conference on games based learning, ECGBL 2024

作者： Healy, Pat Xu, Andrew Pho, Angeline You, Kai-Lin Babichenko, Dmitriy Malizio, Isabelle Thomas, Teresa Hagan School of Computing and Information University of Pittsburgh Pittsburgh United States School of Nursing University of Pittsburgh Pittsburgh United States

ISBN: (纸本)9781917204194

Narrative-based serious games are accessible, engaging technologies that connect users’ lived experiences to pedagogy. Despite having patient-centered goals, most narrative-based serious games are not designed alongside patients and communities, limiting their likelihood of acceptance, uptake, and impact. Literature reveals that many serious games intended for patients merely evaluate efficacy with end-users after game deployment and with a lack of consistent participatory design. This work aims to describe a patient-centered participatory approach to game development to teach self-advocacy skills to patients newly diagnosed with cancer. First, characters were developed based on panels that included patient advocates, cancer survivors, clinicians, and researchers. Second, storyline development created realistic story arcs, decision-points, and consequences based on qualitative interviews with patients, patient advocates, and cancer survivors. Third, game evaluation metrics (e.g., 1st vs. 3rd person perspective, game fail states that incentivize replaying the game, and provision of implicit or explicit feedback) were developed based on accessibility, usability, and patient preferences. based on patients’ insights, we implemented changes accordingly to maximize the game’s efficacy and collected qualitative data on patients’ assessment of the game’s accessibility, relevance, and impact. During initial game development, patient and advocate feedback built relatable characters with a particular focus on providing sensitive information (e.g., palliative care) and inclusive storylines (e.g., diverse family situations). Following a prototype, patients and advocates suggested refinements to characters and additional storylines, including common and/or distressing experiences related to pain management, family dynamics, financial struggles, and disrespect from healthcare providers. Participants in a randomized trial of the game (N=34) found the scenarios relevant and realisti

关键词： Diseases

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Designing Educational Board games of Global Anthropogenic Issues Through Interdisciplinary Collaboration 26th

Designing Educational Board Games of Global Anthropogenic Is...

引用

26th International conference on Interactive Collaborative learning (ICL) - Towards a Hybrid, Flexible and Socially Engaged Higher Education / 52nd IGIP International conference on Engineering Pedagogy

作者： Kengo, Suzuki Syun-ichi, Urayama Yusuke, Hirai Takuto, Yamaguchi Kiyokazu, Ujiie Hajime, Akiyama Univ Tsukuba Tenno Dai I-1-1 Tsukuba Ibaraki Japan ARARE STUDIO Ltd Tsukuba Ibaraki Japan

ISBN: (纸本)9783031530210;9783031530227

To contribute to the mitigation of global anthropogenic crises, engineering education needs to provide holistic views of these crises through collaborating with experts in various fields. This study designed three educational board games representing common structures among global anthropogenic issues and investigated their effects on the lessons learned by university students. Experts in Energy System Engineering, Virology, Philosophy of Education, Design Science, Agricultural Economics, and Law participated in this study. The 2nd, 3rd, and 4th authors of this study designed games named 'Parasite Wars', 'The Dialogue with Future', and 'The House". The concept of games, such as themes, roles and purposes of players, and lessons expected to be imparted to participants, largely differed among the games;each designer represented the same issues from very different perspectives. The results of test sessions with 60 students suggest that participants learned lessons relevant to the messages that the designers conveyed. Further, discussions and reviews for designing board games are useful to understand the perspectives and approaches of experts in other fields and reflect on the roles of their own disciplines in terms of sustainability education. Such interdisciplinary collaboration enables the design of educational content that complements diverse perspectives on global anthropogenic issues and has the potential to help promote a holistic view of such complex issues.

关键词： Game-based learning Interdisciplinary Collaboration Anthropocene

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Proceedings - 2024 3rd International conference on Artificial Intelligence and Software Engineering, ICAISE 2024

Proceedings - 2024 3rd International Conference on Artificia...

引用

3rd International conference on Artificial Intelligence and Software Engineering, ICAISE 2024

ISBN: (纸本)9798331532864

The proceedings contain 11 papers. The topics discussed include: improved YOLOv5-based method for date palm leaf disease recognition;three real-time pathfinding strategies in games: from a ideas to machine learning approaches;software metrics selection– the case of C#;automated seismic horizon picking using vision transformer;a regionally generalized machine learning framework towards census-enabled multi-factor non-communicable disease analyses;and enhancing the customer experience in Philippine food court establishments with an integrated self-service ordering system.

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Design of Intelligent System for Puzzle games based on Machine learning 3

Design of Intelligent System for Puzzle Games Based on Machi...

引用

3rd IEEE International conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Jiang, Xinli Fu, Peng Center Of Well-being Training Changchun Humanities And Sciences College Changchun China

ISBN: (纸本)9798350318609

In terms of data processing in puzzle games, this research paper studies and implements a set of data table workflows, with the aim of improving the flexibility of data configuration and increasing the convenience of data export, runtime loading, and data usage. This article implements a puzzle game framework that encapsulates the underlying modules and provides support for the upper logic modules. The three most important and commonly used modules in game frameworks are: state machine module, resource management module, and log module. The research results indicate that based on the puzzle game framework, the development efficiency of logical functions has been greatly improved, and the portability of the code has been greatly enhanced. Through overall testing, it can be seen from the overall performance that the game client is running well, and all parts meet the expected requirements. It also meets the requirements in non-functional aspects such as performance. © 2024 IEEE.

关键词： Intelligent systems

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Three Real-Time Pathfinding Strategies in games: From A∗ Ideas to Machine learning Approaches 3

Three Real-Time Pathfinding Strategies in Games: From A∗ Id...

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3rd International conference on Artificial Intelligence and Software Engineering, ICAISE 2024

作者： Hong, Xinyu Hu, Xingran Lin, Yixing Fuzhou University Fuzhou China Tianjin Normal University Tianjin China South China Normal University Guangzhou Foshan China

ISBN: (纸本)9798331532864

As the complexity of video games escalates, the presence of more agents, diverse game environments and richer game mechanisms are continuously drawing attention to real-time pathfinding algorithms. Researchers have delved into enhancing traditional algorithms to reduce the time cost in discovering a satisfying path. based on the classic A∗ algorithm, new variants, including Time-Bound A∗ algorithm (TBA*), are proposed and achieved better performance than the traditional version. Additionally, reinforcement learning techniques, including Monte Carlo Tree Search, have been implemented to mitigate environmental dependency in games. Furthermore, based on the classification prowess of neural networks, several deep learning approaches like MAPFASTER use neural networks as selectors of pathfinding algorithms. In this work, these three approaches are discussed, including their ideas, principles, merits, limitations, contributions and prospective. This paper offers comprehensive insights and can serve as a reference for researchers investigating real-time pathfinding algorithms that integrate multiple domains. © 2024 IEEE.

关键词： Deep reinforcement learning

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Non-Intrusive Experimental Behavior Monitoring System based on Pre-Trained Model 24

Non-Intrusive Experimental Behavior Monitoring System Based ...

引用

3rd International conference on Artificial Intelligence and Education, ICAIE 2024

作者： Liu, Ying Tu, Jiajun He, Xiapeng Hu, Jianpeng Shanghai University of Engineering Science Shanghai China

ISBN: (纸本)9798400712692

Traditional electronic classroom software is widely used in teaching university computer labs. When the teacher lectures in front of the classroom, he/she cannot see all the students' learning behaviors. Thus the students like playing computer games, which undoubtedly increases the teacher's workload. To address above problems, we designed a non-intrusive student behavior monitoring system. This system collects a lot of images of students' screens on the teacher's computer through a data acquisition device. The images are processed by the image processing techniques and the pre-trained model. If non-learning behaviors are detected, the system sends the results to the teacher, who can stop students from doing these behaviors. The system not only reduces the teacher's teaching workload but also improves the studying atmosphere. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Legacy systems

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Transfer learning for Cricket Shot Classification: An Inception-v3 Approach 3

Transfer Learning for Cricket Shot Classification: An Incept...

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3rd IEEE International conference on Data, Decision and Systems, ICDDS 2024

ISBN: (纸本)9798350363890

Deep learning finds its application in multiple disciplines from healthcare to security systems. Convolution neural networks a part of deep learning architecture power the computers with human visionary capabilities. Its application in the sports industry has changed the landscape of coaching by providing real-time analysis of player shots and helping prevent players from getting injured based on pose estimation techniques. Cricket is one of the most popular games across the world that involves immense concentration and hand-eye coordination skills to excel in the game. The integration of Convolutional Neural Networks (CNNs) with cricket has evolved the game to the next level in recent years. In this work, we build a CNN model using transfer learning methods to classify four different batting shots based on their specific movements. We used the popular Kaggle cricket shots dataset which consists of 4723 images that belong to any of the four batting shots. Inception-v3, a pre-trained convolutional neural network model that was trained on the ImageNet dataset was utilized because of its deep neural network capabilities while efficiently using computational resources. Once after training the model using different sets of hyperparameters, our model achieved an accuracy of 98.7% on the provided test dataset and showed impressive results in other performance metrics as well. © 2024 IEEE.

关键词： Cricket (Sports)

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Q-learning for Stackelberg games of Uncertain Nonlinear Systems 3

Q-Learning for Stackelberg Games of Uncertain Nonlinear Syst...

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3rd International conference on Service Robotics, ICoSR 2024

作者： Tang, Wenbei Cui, Xiaohong Sun, Jun Deng, Jiaxian The College of Mechanical and Electrical Engineering China Jiliang University Hangzhou China China Jiliang University Zhejiang Province Key Laboratory of On-line Testing Equipment Calibration Technology Research Hangzhou China

ISBN: (纸本)9798350367119

The Stackelberg equilibrium approach is based on the traditional dynamic programming technique, which requires an understanding of the system model to solve the optimal control problem. Therefore, we propose a Q-learning algorithm based on actor-critic structure to solve the optimization problem of Stackelberg game in nonlinear systems with unknown system model data. Currently, the Q-learning algorithm is mainly used in the study of linear systems in this direction, and the study of nonlinear system problems is limited. In addition, the stability of the system is ensured by proving the consistency of the system state and the ultimate boundedness of the neural network weight estimation error. Finally, the effectiveness of the algorithm is verified by simulation experiment. © 2024 IEEE.

关键词： Dynamic programming

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