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Research map / Probabilistic and scientific modeling / Variational and generative sampling

Planning with Hidden Parameter Polynomial MDPs

AAAI 2023 · Probabilistic and scientific modeling › Variational and generative sampling · approach: Exact inference for probabilistic programs · 7 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use a closed-form polynomial belief instead of a particle-based beliefBAMCP · Grid5Mean CostHelped
Use a closed-form polynomial belief instead of a particle-based beliefBAMCP · SeaGridMean Cost: 17.6± 0.435; 58.7± 3.64; 50.3± 3.53; 37.5± 3.32; 49.6± 2.64; 55.2± 2.85; 48.8± 2.52; 44.1± 2.73; 41.8± 2.71Helped
Use a closed-form polynomial belief instead of a particle-based beliefBAMCP · SeaGridFailure Rate: 0.0; 1.0; 1.0; 0.85; 0.85; 0.9; 0.74; 0.8; 0.64; 0.74; 0.77Helped
Increase the number of particles used to represent the beliefBAMCP-G and BAMCP-PF · Grid5Mean CostMixed

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