6 citations · 30 across the 14 of their papers we have counts for
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cs.AI2023★ 3 cited
Learning Logic Specifications for Soft Policy Guidance in POMCP
Giulio Mazzi, Daniele Meli, Alberto Castellini +1
Partially Observable Monte Carlo Planning (POMCP) is an efficient solver for Partially Observable Markov Decision Processes (POMDPs). It allows scaling to large state spaces by com…
cs.RO2023★ 6 cited
Unsupervised Active Visual Search with Monte Carlo planning under Uncertain Detections
Francesco Taioli, Francesco Giuliari, Yiming Wang +6
We propose a solution for Active Visual Search of objects in an environment, whose 2D floor map is the only known information. Our solution has three key features that make it more…