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@jemoka / Jemoka Knowledge Base / wiki/concepts/adaops.md
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--- title: "AdaOPS" type: concept related: [Kl Divergence] source: https://www.jemoka.com/posts/kbhadaops/ confidence: high status: active --- How do you sample particle filters? This doesn’t work for a continuous action space. Contributions Uses KLD sampling—adaptive sampling of particple filters “belief packing”—pack similar beliefs together, making observation tree smaller KLD Sampling KLD Sampling uses KL Divergence to approximate difference between two probability distributions: \begin{equation} N \approx \frac{k-1}{2\xi} \qty(1- \frac{2}{9(k-1)} + \sqrt{\frac{2}{9(k-1)}} z_{1-\eta})^{3} \end{equation} “Propagation” We want to get a set of sampled observations from belief + action. Belief Packing L1 norm between beliefs. If its too small consider them the same beliefs.