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Windowed A-K-MDP
Markov decision processes (MDPs) are used to support decision-making in conservation of biodiversity, but policies, even over small state spaces, can be difficult to interpret for conservation managers. K-MDP methods address this problem by building simpler MDPs with at most K abstract states. We show that the previously proposed A-K-MDP algorithm that relies on selecting a discretisation divisor using binary search can skip better abstract states. To fix this issue, we propose Windowed A-K-MDP, an algorithm that generates every distinct feasible partition induced within a declared divisor win
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-12T03:01:17.000Z
First collected: 2026-09-20T16:41:15.630Z. This is not the publication date.