SLOPE improves MBRL in sparse reward settings by using optimistic distributional regression to build informative potential landscapes that provide better exploration gradients, outperforming baselines across 30+ tasks and real robotic deployments.
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SLOPE: Optimistic Potential Landscape Shaping for Model-based Reinforcement Learning
SLOPE improves MBRL in sparse reward settings by using optimistic distributional regression to build informative potential landscapes that provide better exploration gradients, outperforming baselines across 30+ tasks and real robotic deployments.