3 papers
cs.LG2025
Simulation Priors for Data-Efficient Deep Learning
Lenart Treven, Bhavya Sukhija, Jonas Rothfuss +3
How do we enable AI systems to efficiently learn in the real-world? First-principles models are widely used to simulate natural systems, but often fail to capture real-world comple…
cs.LG2023
Efficient Exploration in Continuous-time Model-based Reinforcement Learning
Lenart Treven, Jonas Hübotter, Bhavya Sukhija +2
Reinforcement learning algorithms typically consider discrete-time dynamics, even though the underlying systems are often continuous in time. In this paper, we introduce a model-ba…
cs.LG2023
Hallucinated Adversarial Control for Conservative Offline Policy Evaluation
Jonas Rothfuss, Bhavya Sukhija, Tobias Birchler +2
We study the problem of conservative off-policy evaluation (COPE) where given an offline dataset of environment interactions, collected by other agents, we seek to obtain a (tight)…