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We study the quality of outcomes in repeated games when the population of players is dynamically changing and participants use learning algorithms to adapt to the changing environment. Game theory classically considers Nash equilibria of…

Computer Science and Game Theory · Computer Science 2020-05-25 Thodoris Lykouris , Vasilis Syrgkanis , Eva Tardos

Objectives: When students use generative AI in coursework, what are its persistent effects on their intellectual development? We investigate (RQ1-How) how students' trust in and routine use of genAI affect their cognitive engagement habits…

Human-Computer Interaction · Computer Science 2026-04-14 Rudrajit Choudhuri , Christopher Sanchez , Margaret Burnett , Anita Sarma

The offline datasets for imitation learning (IL) in multi-agent games typically contain player trajectories exhibiting diverse strategies, which necessitate measures to prevent learning algorithms from acquiring undesirable behaviors.…

Multiagent Systems · Computer Science 2025-02-17 Shiqi Lei , Kanghoon Lee , Linjing Li , Jinkyoo Park

Meta-reinforcement learning (Meta-RL) facilitates rapid adaptation to unseen tasks but faces challenges in long-horizon environments. Skill-based approaches tackle this by decomposing state-action sequences into reusable skills and…

Machine Learning · Computer Science 2026-05-21 Sanghyeon Lee , Sangjun Bae , Yisak Park , Seungyul Han

Many people learn programming independently from online resources and often report struggles in achieving their personal learning goals. Learners frequently describe their experiences as isolating and frustrating, challenged by abundant…

Human-Computer Interaction · Computer Science 2025-07-31 Sami Saeed Alghamdi , Christopher Bull , Ahmed Kharrufa

Over the last three decades, various didactic proposals have been published in an attempt to connect theory and research findings with the design of Teaching-Learning Sequences (TLS) in various contexts. Many studies have analysed the…

Physics Education · Physics 2024-04-23 Jenaro Guisasola , Kristina Zuza , Jaume Ametller , Paulo Sarriugarte

We initiate the study of structured Stackelberg games, a novel form of strategic interaction between a leader and a follower where contextual information can be predictive of the follower's (unknown) type. Motivated by applications such as…

Computer Science and Game Theory · Computer Science 2026-05-18 Maria-Florina Balcan , Kiriaki Fragkia , Keegan Harris

This study examined the effects of a technology-enhanced intervention on the self-regulation of 262 eighth-grade students, employing information and communication technology (ICT) and web-based self-assessment tools set against science…

Human-Computer Interaction · Computer Science 2024-04-16 Chi-Jung Sui , Miao-Hsuan Yen , Chun-Yen Chang

Our paper is research in progress that is research investigating the use of games technology to enhance the learning of a physical skill. The Microsoft Kinect is a system designed for gaming with the capability to track the movement of…

Computers and Society · Computer Science 2016-06-14 Kirsten Ellis , Julie Fisher , Louisa Willoughby , Jan Carlo Barca

Significant research work has been undertaken related to the game-based learning approach over the last years. However, a closer look at this work reveals that further research is needed to examine some types of game-based learning…

Computers and Society · Computer Science 2024-07-02 Aldo Gordillo , Daniel López-Fernández , Jesús Mayor

Dynamic Reinforcement Learning (Dynamic RL), proposed in this paper, directly controls system dynamics, instead of the actor (action-generating neural network) outputs at each moment, bringing about a major qualitative shift in…

Machine Learning · Computer Science 2025-02-17 Katsunari Shibata

E-learning is a widely used learning method, but with the development of society, traditional E-learning method has exposed some shortcomings, such as the boring way of teaching, so that it is difficult to increase the enthusiasm of…

Computers and Society · Computer Science 2022-01-19 Huansheng Ning , Hang Wang , Wenxi Wang , Xiaozhen Ye , Jianguo Ding , Per Backlund

Whenever students use any drilling system the question arises how much of their learning is meaningful learning vs memorisation through repetition or rote learning. Although both types of learning have their place in an educational system…

Strategic recommendations (SR) refer to the problem where an intelligent agent observes the sequential behaviors and activities of users and decides when and how to interact with them to optimize some long-term objectives, both for the user…

Machine Learning · Computer Science 2020-09-17 Georgios Theocharous , Yash Chandak , Philip S. Thomas , Frits de Nijs

Gamification is an effective strategy for motivating and engaging users, which is grounded in business, marketing, and management by designing games in nongame contexts. Gamifying education, which consists of the design and study of…

General Economics · Economics 2025-08-11 Jiasheng Zhu , Luyao Zhang

In many settings of interest, a policy is set by one party, the leader, in order to influence the action of another party, the follower, where the follower's response is determined by some private information. A natural question to ask is,…

Computer Science and Game Theory · Computer Science 2025-04-23 Michael Albert , Quinlan Dawkins , Minbiao Han , Haifeng Xu

When a game involves many agents or when communication between agents is not possible, it is useful to resort to distributed learning where each agent acts in complete autonomy without any information on the other agents' situations.…

Optimization and Control · Mathematics 2025-09-24 Jérôme Taupin , Xavier Leturc , Christophe J. Le Martret

Wargames are simulations of conflicts in which participants' decisions influence future events. While casual wargaming can be used for entertainment or socialization, serious wargaming is used by experts to explore strategic implications of…

Artificial Intelligence · Computer Science 2025-10-24 Glenn Matlin , Parv Mahajan , Isaac Song , Yixiong Hao , Ryan Bard , Stu Topp , Evan Montoya , M. Rehan Parwani , Soham Shetty , Mark Riedl

General game testing relies on the use of human play testers, play test scripting, and prior knowledge of areas of interest to produce relevant test data. Using deep reinforcement learning (DRL), we introduce a self-learning mechanism to…

Machine Learning · Computer Science 2021-03-31 Joakim Bergdahl , Camilo Gordillo , Konrad Tollmar , Linus Gisslén

The integration of Generative AI (GenAI) into education has raised concerns about over-reliance and superficial learning, particularly in writing tasks in higher education. This study explores whether a theory-driven learning analytics…

Human-Computer Interaction · Computer Science 2025-06-25 Angxuan Chen , Jingjing Lian , Xinran Kuang , Jiyou Jia
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