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cs.LG2026
Trajectory Design and Budgeted Querying for Digital Twin Calibration
Vladyslava Spitkovska, Dmytro Kuzmenko
Digital-twin calibration requires interaction data that is expensive to collect. We study two acquisition decisions: which trajectories to generate, and when to spend a limited bud…
cs.LG2025
TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents
Dmytro Kuzmenko, Nadiya Shvai
We present a novel approach to knowledge transfer in model-based reinforcement learning, addressing the critical challenge of deploying large world models in resource-constrained e…
cs.LG2025
Knowledge Transfer in Model-Based Reinforcement Learning Agents for Efficient Multi-Task Learning
Dmytro Kuzmenko, Nadiya Shvai
We propose an efficient knowledge transfer approach for model-based reinforcement learning, addressing the challenge of deploying large world models in resource-constrained environ…