Utilizing Priors in Sampling-based Cost Minimization
<|reference_start|>Utilizing Priors in Sampling-based Cost Minimization: We consider an autonomous vehicle (AV) agent performing a long-term cost-minimization problem in the elapsed time $T$ over sequences of states $s_{1:T}$ and actions $a_{1:T}$ for some fixed, known (though potentially learned) cost function $C(s_t,a_t)$, approximate system dynamics $P$, and distribution over initial states $d_0$. The goal is to minimize the expected cost-to-go of the driving trajectory $\tau = s_1, a_1, ..., s_T, a_T$ from the initial state.<|reference_end|>
@article{lou2024utilizing,
    title={Utilizing Priors in Sampling-based Cost Minimization},
    author={Yuan-Yao Lou, Jonathan Spencer, Kwang Taik Kim, Mung Chiang},
    journal={arXiv preprint arXiv:2409.19834},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.19834},
    primaryClass={eess.SY cs.SY}
}