Cheating and detection method in massively multiplayer online role-playing game: systematic literature review
Recently, despite massively multiplayer online role-playing game (MMORPG) based on the
PC implementation environment in mobile games, related fraudulent and illegal activities …
PC implementation environment in mobile games, related fraudulent and illegal activities …
[HTML][HTML] Investigating the knowledge structure of research on massively multiplayer online role-playing games: A bibliometric analysis
As the concept of the Metaverse rapidly spread, massively multiplayer online role-playing
game (MMORPG), one of the Metaverse games, received public's attention again …
game (MMORPG), one of the Metaverse games, received public's attention again …
Individual-level inverse reinforcement learning for mean field games
The recent mean field game (MFG) formalism has enabled the application of inverse
reinforcement learning (IRL) methods in large-scale multi-agent systems, with the goal of …
reinforcement learning (IRL) methods in large-scale multi-agent systems, with the goal of …
Weighted mean-field multi-agent reinforcement learning via reward attribution decomposition
Existing MARL algorithms have low efficiency in many-agent scenarios due to the complex
dynamic interaction when agents growing exponentially. Mean-field theory has been …
dynamic interaction when agents growing exponentially. Mean-field theory has been …
Market Interventions in a Large-Scale Virtual Economy
Massively multiplayer online role-playing games often contain sophisticated in-game
economies. Many important real-world economic phenomena, such as inflation, economic …
economies. Many important real-world economic phenomena, such as inflation, economic …
[图书][B] Learning in Mean-Field Games and Continuous-Time Stochastic Control Problems
A Hu - 2022 - search.proquest.com
In recent years, there has been an ever-increasing demand for building reliable and
versatile agents in applications arising from numerous fields including autonomous driving …
versatile agents in applications arising from numerous fields including autonomous driving …
From One to Infinity: New Algorithms for Reinforcement Learning and Inverse Reinforcement Learning
Y Chen - 2022 - researchspace.auckland.ac.nz
bandit algorithm that achieves a good trade-off in this complex environment setting, which
was previously challenging to handle. Then, for the multi-agent case, we develop an MARL …
was previously challenging to handle. Then, for the multi-agent case, we develop an MARL …
Game-bot Detection based on Analysis of Harvest Coordinate
JW Choi, AR Kang - Journal of The Korea Society of Computer and …, 2022 - koreascience.kr
As the online game market grows, the use of game bots is causing the most serious problem
for game services. We propose a harvest coordinate analysis model to detect harvesting …
for game services. We propose a harvest coordinate analysis model to detect harvesting …
채집좌표분석기반게임봇탐지
최재웅， 강아름 - 한국컴퓨터정보학회논문지, 2022 - dbpia.co.kr
온라인 게임 시장이 성장하면서 게임 봇의 사용은 게임 서비스에 가장 심각한 문제를 야기하고
있다. 본 논문에 서는 MMORPG 장르의 게임 봇 중 채집을 진행하는 봇을 탐지하기 위한 채집 …
있다. 본 논문에 서는 MMORPG 장르의 게임 봇 중 채집을 진행하는 봇을 탐지하기 위한 채집 …