2 papers
cs.LG2025
Neural Risk-sensitive Satisficing in Contextual Bandits
Shogo Ito, Tatsuji Takahashi, Yu Kono
The contextual bandit problem, which is a type of reinforcement learning tasks, provides an effective framework for solving challenges in recommendation systems, such as satisfying…
cs.LG2024
Reinforcement Learning with a Focus on Adjusting Policies to Reach Targets
Akane Tsuboya, Yu Kono, Tatsuji Takahashi
The objective of a reinforcement learning agent is to discover better actions through exploration. However, typical exploration techniques aim to maximize rewards, often incurring…