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cs.LG2026
Explore Beyond the Boundary Using Entropic Information
Bumgeun Park, Donghwan Lee
In reinforcement learning, exploration with sparse and delayed rewards presents a significant challenge due to the limited feedback available for guiding the learning process. Addr…
cs.LG2025
Adaptive Policy Backbone via Shared Network
Bumgeun Park, Donghwan Lee
Reinforcement learning (RL) has achieved impressive results across domains, yet learning an optimal policy typically requires extensive interaction data, limiting practical deploym…
cs.LG2025
Deep Q-Learning with Gradient Target Tracking
Bum Geun Park, Taeho Lee, Donghwan Lee
This paper introduces Q-learning with gradient target tracking, a novel reinforcement learning framework that provides a learned continuous target update mechanism as an alternativ…