Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Park, Kwanyoung"'
Unsupervised goal-conditioned reinforcement learning (GCRL) is a promising paradigm for developing diverse robotic skills without external supervision. However, existing unsupervised GCRL methods often struggle to cover a wide range of states in comp
Externí odkaz:
http://arxiv.org/abs/2407.08464
Autor:
Park, Kwanyoung, Lee, Youngwoon
Model-based offline reinforcement learning (RL) is a compelling approach that addresses the challenge of learning from limited, static data by generating imaginary trajectories using learned models. However, it falls short in solving long-horizon tas
Externí odkaz:
http://arxiv.org/abs/2407.00699
Autor:
Park, Junseok, Park, Kwanyoung, Oh, Hyunseok, Lee, Ganghun, Lee, Minsu, Lee, Youngki, Zhang, Byoung-Tak
Critical periods are phases during which a toddler's brain develops in spurts. To promote children's cognitive development, proper guidance is critical in this stage. However, it is not clear whether such a critical period also exists for the trainin
Externí odkaz:
http://arxiv.org/abs/2201.04990
Building human-like agent, which aims to learn and think like human intelligence, has long been an important research topic in AI. To train and test human-like agents, we need an environment that imposes the agent to rich multimodal perception and al
Externí odkaz:
http://arxiv.org/abs/2105.00762
One of the inherent limitations of current AI systems, stemming from the passive learning mechanisms (e.g., supervised learning), is that they perform well on labeled datasets but cannot deduce knowledge on their own. To tackle this problem, we deriv
Externí odkaz:
http://arxiv.org/abs/2101.11221