10 citations · 12 across the 9 of their papers we have counts for
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cs.AI2023
Game Solving with Online Fine-Tuning
Ti-Rong Wu, Hung Guei, Ting Han Wei +3
Game solving is a similar, yet more difficult task than mastering a game. Solving a game typically means to find the game-theoretic value (outcome given optimal play), and optional…
cs.AI2023★ 1 cited
Residual Scheduling: A New Reinforcement Learning Approach to Solving Job Shop Scheduling Problem
Kuo-Hao Ho, Ruei-Yu Jheng, Ji-Han Wu +4
Job-shop scheduling problem (JSP) is a mathematical optimization problem widely used in industries like manufacturing, and flexible JSP (FJSP) is also a common variant. Since they…
cs.AI2023
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…