arxiv
PublishedJuly 22, 2026 at 4:00 AM
—neutral
Toward Learning POMDPs Beyond Full-Rank Actions and State Observability
Publisher summary· verbatim
arXiv:2601.18930v4 Announce Type: replace-cross Abstract: We are interested in enabling autonomous agents to learn and reason about systems with hidden states, such as locking mechanisms. We cast this problem as learning the parameters of a discrete Partially Observable Markov Decision Process (POMD
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Originally published on arxiv ↗