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Kuo-Hao Ho

2 accepted papers

2025

Learning Human-Like RL Agents Through Trajectory Optimization With Action Quantization

NeurIPS 2025poster

Human-like agents have long been one of the goals in pursuing artificial intelligence. Although reinforcement learning (RL) has achieved superhuman performance in many domains, relatively little attention has been focused on designing human-like RL agents. As a result, many reward-driven RL agents o…

Cited by 0SourceScholar
2024

PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping

AAAI 2024technical

Proximal Policy Optimization algorithm employing a clipped surrogate objective (PPO-Clip) is a prominent exemplar of the policy optimization methods. However, despite its remarkable empirical success, PPO-Clip lacks theoretical substantiation to date. In this paper, we contribute to the field by est…

Cited by 13SourcePDFScholar