Adaptive Sampling using POMDPs with Domain-Specific Considerations
Gautam Salhotra,Christopher E. Denniston,David A. Caron,Gaurav S. Sukhatme,Gautam Salhotra,Christopher E. Denniston,David A. Caron,Gaurav S. Sukhatme
We investigate improving Monte Carlo Tree Search based solvers for Partially Observable Markov Decision Processes (POMDPs), when applied to adaptive sampling problems. We propose improvements in rollout allocation, the action exploration algorithm, and plan commitment. The first allocates a different number of rollouts depending on how many actions the agent has taken in an episode. We find that r...
