2 papers
cs.AI2024
Acting upon Imagination: when to trust imagined trajectories in model based reinforcement learning
Adrian Remonda, Eduardo Veas, Granit Luzhnica
Model-based reinforcement learning (MBRL) aims to learn model(s) of the environment dynamics that can predict the outcome of its actions. Forward application of the model yields so…
cs.RO2024
A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data
Adrian Remonda, Nicklas Hansen, Ayoub Raji +4
Despite the availability of international prize-money competitions, scaled vehicles, and simulation environments, research on autonomous racing and the control of sports cars opera…