Methods and Systems for Multi Agent Pathfinding
Abstract
Methods, and systems, for Multiagent Pathfinding for Non
Dynamic Progrannning Problems, including a CE method
which provides for sampling from a complex probability
distribution that is not necessarily known in a closed form.
The applications of this method include rare-event simulation,
variance reduction for estimation problems, and stochastic
optimization. The method iteratively searches for a
probability distribution that is "close" to the intended distribution,
where the closeness of distributions is measured
using the Kullback-Liebler (KL) divergence between the
distributions. At each step, the method generates samples
according to a current candidate distribution from the family.
Next, it uses those current candidate distribution samples to
move the distribution toward a new candidate distribution
that is closer in the sense of KL divergence to the target
distribution.
Rights
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