2 citations · 2 across the 4 of their papers we have counts for
7 papers
Two Perfect One-Factorizations of
Tomasz Maciosowski
A perfect 1-factorization of the complete graph is a partition of its edges into perfect matchings such that the union of any two of them is a Hamilton cycle. Kotzig conje…
BooST: Bridging Semantics and Motions for Efficient Skill Transfer
Jusuk Lee, Daesol Cho, Jonghun Shin +4
Skill abstraction---the process of learning reusable and temporally extended behaviors---has emerged as a key paradigm for improving sample efficiency and generalization in robot l…
FLAG: Flow Policy MaxEnt-RL by Latent Augmented Guidance
Sungha Kim, Gawon Lee, Jusuk Lee +3
Maximum entropy reinforcement learning (MaxEnt-RL) enables robust exploration, yet practical implementations often restrict policies to simple Gaussians. While recent approaches in…
Temporal Action Representation Learning for Tactical Resource Control and Subsequent Maneuver Generation
Hoseong Jung, Sungil Son, Daesol Cho +3
Autonomous robotic systems should reason about resource control and its impact on subsequent maneuvers, especially when operating with limited energy budgets or restricted sensing.…
Periodic Skill Discovery
Jonghae Park, Daesol Cho, Jusuk Lee +3
Unsupervised skill discovery in reinforcement learning (RL) aims to learn diverse behaviors without relying on external rewards. However, current methods often overlook the periodi…
EigenSafe: A Spectral Framework for Learning-Based Probabilistic Safety Assessment
Inkyu Jang, Jonghae Park, Sihyun Cho +3
We present EigenSafe, an operator-theoretic framework for safety assessment of learning-enabled stochastic systems. In many robotic applications, the dynamics are inherently stocha…
CQM: Curriculum Reinforcement Learning with a Quantized World Model
Seungjae Lee, Daesol Cho, Jonghae Park +1
Recent curriculum Reinforcement Learning (RL) has shown notable progress in solving complex tasks by proposing sequences of surrogate tasks. However, the previous approaches often…