345 citations · 493 across the 2 of their papers we have counts for
2 papers
cs.AI2013★ 345 cited
Incremental Pruning: A Simple, Fast, Exact Method for Partially Observable Markov Decision Processes
Anthony R. Cassandra, Michael L. Littman, Nevin Lianwen Zhang
Most exact algorithms for general partially observable Markov decision processes (POMDPs) use a form of dynamic programming in which a piecewise-linear and convex representation of…
cs.AI2013★ 148 cited
Solving POMDPs by Searching the Space of Finite Policies
Nicolas Meuleau, Kee-Eung Kim, Leslie Pack Kaelbling +1
Solving partially observable Markov decision processes (POMDPs) is highly intractable in general, at least in part because the optimal policy may be infinitely large. In this paper…