Discrete Prompt Compression with Reinforcement Learning

1 code implementation • 17 Aug 2023 • Hoyoun Jung, Kyung-Joong Kim

In addition, we demonstrate that the learned policy can be transferred to larger LMs, and through a comprehensive analysis, we explore the token importance within the prompts.

Decoder reinforcement-learning

RaidEnv: Exploring New Challenges in Automated Content Balancing for Boss Raid Games

no code implementations • 4 Jul 2023 • Hyeon-Chang Jeon, In-Chang Baek, Cheong-mok Bae, Taehwa Park, Wonsang You, Taegwan Ha, Hoyun Jung, Jinha Noh, Seungwon Oh, Kyung-Joong Kim

These benchmarks address two open problems in automatic content balancing, and we introduce two evaluation metrics to provide guidance for AI in automatic content balancing.

Behavioral Differences is the Key of Ad-hoc Team Cooperation in Multiplayer Games Hanabi

no code implementations • 12 Mar 2023 • Hyeonchang Jeon, Kyung-Joong Kim

Ad-hoc team cooperation is the problem of cooperating with other players that have not been seen in the learning process.

Clustering Reinforcement Learning (RL)

Game Data Mining Competition on Churn Prediction and Survival Analysis using Commercial Game Log Data

no code implementations • 7 Feb 2018 • Kyung-Joong Kim, DuMim Yoon, JiHoon Jeon, Seong-il Yang, Sang-Kwang Lee, EunJo Lee, Yoonjae Jang, Dae-Wook Kim, Pei Pei Chen, Anna Guitart, Paul Bertens, África Periáñez, Fabian Hadiji, Marc Müller, Youngjun Joo, Jiyeon Lee, Inchon Hwang

Game companies avoid sharing their game data with external researchers.

Databases