2 papers
cs.RO2026
ResWM: Residual-Action World Model for Visual RL
Jseen Zhang, Gabriel Adineera, Jinzhou Tan +1
Learning predictive world models from raw visual observations is a central challenge in reinforcement learning (RL), especially for robotics and continuous control. Conventional mo…
cs.LG2026
ProgAgent:A Continual RL Agent with Progress-Aware Rewards
Jinzhou Tan, Gabriel Adineera, Jinoh Kim
We present ProgAgent, a continual reinforcement learning (CRL) agent that unifies progress-aware reward learning with a high-throughput, JAX-native system architecture. Lifelong ro…