4 papers
When Plans Change, Remember: Replanning-Guided Visual Memory for Vision-Language-Action Models
Victoria Smelova, Daniil Kazachkov, Georgiy Kazantsev +6
Long-horizon, multi-stage Vision-Language-Action (VLA) policies often require visual information that is no longer present in the current observation. Retaining the complete observ…
Imagine to Ensure Safety in Hierarchical Reinforcement Learning
Gregory Gorbov, Artem Latyshev, Aleksandr I. Panov
This work investigates the safe exploration problem in reinforcement learning, where an agent must maximize cumulative performance while simultaneously satisfying safety constraint…
Safe Planning and Policy Optimization via World Model Learning
Artem Latyshev, Gregory Gorbov, Aleksandr I. Panov
Reinforcement Learning (RL) applications in real-world scenarios must prioritize safety and reliability, which impose strict constraints on agent behavior. Model-based RL leverages…
Intrinsic Motivation in Model-based Reinforcement Learning: A Brief Review
Artem Latyshev, Aleksandr I. Panov
The reinforcement learning research area contains a wide range of methods for solving the problems of intelligent agent control. Despite the progress that has been made, the task o…