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Found 2 papers, 1 papers with code
Effective Baselines for Multiple Object Rearrangement Planning in Partially Observable Mapped Environments
This requires efficient trade-offs between exploration of the environment and planning for rearrangement, which is challenging because of long-horizon nature of the problem.
An End-to-end Deep Reinforcement Learning Approach for the Long-term Short-term Planning on the Frenet Space
Tactical decision making and strategic motion planning for autonomous highway driving are challenging due to the complication of predicting other road users' behaviors, diversity of environments, and complexity of the traffic interactions.
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