Time-bounded mission planning in time-varying domains with semi-MDPS and Gaussian processes
Uncertain, time-varying dynamic environments are ubiquitous in real world robotics. We propose an online planning framework to address time-bounded missions under time-varying dynamics, where those dynamics affect the duration and outcome of actions. We pose such problems as semi-Markov decision pro...
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Journal of Machine Learning Research
2021
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