69 citations · 72 across the 8 of their papers we have counts for
8 papers
Empowering Economic Simulation for Massively Multiplayer Online Games through Generative Agent-Based Modeling
Bihan Xu, Shiwei Zhao, Runze Wu +10
Within the domain of Massively Multiplayer Online (MMO) economy research, Agent-Based Modeling (ABM) has emerged as a robust tool for analyzing game economics, evolving from rule-b…
MVP-Shapley: Feature-based Modeling for Evaluating the Most Valuable Player in Basketball
Haifeng Sun, Yu Xiong, Runze Wu +5
The burgeoning growth of the esports and multiplayer online gaming community has highlighted the critical importance of evaluating the Most Valuable Player (MVP). The establishment…
Digital Player: Evaluating Large Language Models based Human-like Agent in Games
Jiawei Wang, Kai Wang, Shaojie Lin +11
With the rapid advancement of Large Language Models (LLMs), LLM-based autonomous agents have shown the potential to function as digital employees, such as digital analysts, teacher…
Towards Long-term Annotators: A Supervised Label Aggregation Baseline
Haoyu Liu, Fei Wang, Minmin Lin +6
Relying on crowdsourced workers, data crowdsourcing platforms are able to efficiently provide vast amounts of labeled data. Due to the variability in the annotation quality of crow…
Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering
Minghao Zhao, Le Wu, Yile Liang +7
Recent years have witnessed the great accuracy performance of graph-based Collaborative Filtering (CF) models for recommender systems. By taking the user-item interaction behavior…
RL4RS: A Real-World Dataset for Reinforcement Learning based Recommender System
Kai Wang, Zhene Zou, Minghao Zhao +7
Reinforcement learning based recommender systems (RL-based RS) aim at learning a good policy from a batch of collected data, by casting recommendations to multi-step decision-makin…
Personalized Bundle Recommendation in Online Games
Qilin Deng, Kai Wang, Minghao Zhao +5
In business domains, \textit{bundling} is one of the most important marketing strategies to conduct product promotions, which is commonly used in online e-commerce and offline reta…
Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation
Kai Wang, Zhene Zou, Qilin Deng +5
In recent years, there are great interests as well as challenges in applying reinforcement learning (RL) to recommendation systems (RS). In this paper, we summarize three key pract…