6 papers
Playstyle and Artificial Intelligence: An Initial Blueprint Through the Lens of Video Games
Chiu-Chou Lin
Contemporary artificial intelligence (AI) development largely centers on rational decision-making, valued for its measurability and suitability for objective evaluation. Yet in rea…
Online Learning of Counter Categories and Ratings in PvP Games
Chiu-Chou Lin, I-Chen Wu
In competitive games, strength ratings like Elo are widely used to quantify player skill and support matchmaking by accounting for skill disparities better than simple win rate sta…
Identifying and Clustering Counter Relationships of Team Compositions in PvP Games for Efficient Balance Analysis
Chiu-Chou Lin, Yu-Wei Shih, Kuei-Ting Kuo +4
How can balance be quantified in game settings? This question is crucial for game designers, especially in player-versus-player (PvP) games, where analyzing the strength relations…
Perceptual Similarity for Measuring Decision-Making Style and Policy Diversity in Games
Chiu-Chou Lin, Wei-Chen Chiu, I-Chen Wu
Defining and measuring decision-making styles, also known as playstyles, is crucial in gaming, where these styles reflect a broad spectrum of individuality and diversity. However,…
Towards Human-Like RL: Taming Non-Naturalistic Behavior in Deep RL via Adaptive Behavioral Costs in 3D Games
Kuo-Hao Ho, Ping-Chun Hsieh, Chiu-Chou Lin +3
In this paper, we propose a new approach called Adaptive Behavioral Costs in Reinforcement Learning (ABC-RL) for training a human-like agent with competitive strength. While deep r…
An Unsupervised Video Game Playstyle Metric via State Discretization
Chiu-Chou Lin, Wei-Chen Chiu, I-Chen Wu
On playing video games, different players usually have their own playstyles. Recently, there have been great improvements for the video game AIs on the playing strength. However, p…