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20242026
most citedTrust the Model Where It Trusts Itself -- Model-Based Actor-Critic with Uncertainty-Aware Rollout Adaption

2 citations · 3 across the 5 of their papers we have counts for

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Showing 2026 · cs.LGShow all

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cs.LG2026

All Models are Wrong, Knowing Where is Useful: On Model Uncertainty in Reinforcement Learning

Bernd Frauenknecht, Devdutt Subhasish, Artur Eisele +2

Model-based reinforcement learning (MBRL) infers information about the environment from a learned dynamics model and bears the potential to address open problems such as data effic…

cs.LG2026

Learning to Race in Minutes: Infoprop Dyna on the Mini Wheelbot

Devdutt Subhasish, Henrik Hose, Sebastian Trimpe

Reinforcement Learning (RL) has the potential to enable robots with fast, nonlinear, and unstable dynamics to reach the limits of their performance. However, most recent advances r…