POMG algorithm for large-scale pursuit game with partial observation and no communication.
Estimation, filtering, and inference for partially-observed Markov processes via a two-stage algorithm involving gradient descent (with a novel gradient estimate for the particle filter) warm-started by iterated filtering. Original engine behind the pypomp Python package. Source code for a submission; currently R&R at JRSS-B.
Course work for CSE 574 Planning and Learning Methods in AI
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