45 citations · 58 across the 3 of their papers we have counts for
Showing cs.AIShow all
2 papers · 1 filter
cs.AI2015★ 6 cited
Metareasoning for Planning Under Uncertainty
Christopher H. Lin, Andrey Kolobov, Ece Kamar +1
The conventional model for online planning under uncertainty assumes that an agent can stop and plan without incurring costs for the time spent planning. However, planning time is…
cs.AI2012★ 45 cited
A Theory of Goal-Oriented MDPs with Dead Ends
Andrey Kolobov, Mausam, Daniel Weld
Stochastic Shortest Path (SSP) MDPs is a problem class widely studied in AI, especially in probabilistic planning. They describe a wide range of scenarios but make the restrictive…