This paper presents a framework that enables multi-agent systems to learn controllers independently through integral reinforcement learning while guaranteeing modular stability when connected. The framework addresses a gap: existing modular control methods require analytical models and cannot handle learned controllers...
Jie Ren, Bahram Shafai· International journal of res...· 0 citations
The team reports highlight the importance of adapting to the deployment environment while retaining prior capabilities, treating demonstration quality at an appropriate temporal scale, and suppressing errors in inactive robot components, and expose the limitations of offline action-prediction metrics for forecasting cl...
Jiaming Wang, Ji-Zhuo Chen, Di-Wen Liu et al.· 0 citations
TS-Mask VLA is built upon two key designs: a Discrete Diffusion Action Expert equipped with a Bridge Attention conditioning bridge, which enables multi-layer conditioning from the VLM and facilitates more accurate and stable action generation; and a temporal-spatial 2D masking strategy for discrete action tokens that s...
Integral reinforcement learning (IRL) solves the linear quadratic regulator (LQR) problem without requiring the system dynamics matrix, but needs full state measurements. In the absence of states, a dedicated PI observer structure can be used in the learning process, which avoids the limitation of P observer. This pape...
Jie Ren, Bahram Shafai· International Conference on...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
