Corpus ID: 4714424

Hindsight is Only 50/50: Unsuitability of MDP based Approximate POMDP Solvers for Multi-resolution Information Gathering

@article{Arora2018HindsightIO,
  title={Hindsight is Only 50/50: Unsuitability of MDP based Approximate POMDP Solvers for Multi-resolution Information Gathering},
  author={Sankalp Arora and Sanjiban Choudhury and Sebastian A. Scherer},
  journal={ArXiv},
  year={2018},
  volume={abs/1804.02573}
}
  • Sankalp Arora, Sanjiban Choudhury, Sebastian A. Scherer
  • Published 2018
  • Computer Science
  • ArXiv
  • Partially Observable Markov Decision Processes (POMDPs) offer an elegant framework to model sequential decision making in uncertain environments. Solving POMDPs online is an active area of research and given the size of real-world problems approximate solvers are used. Recently, a few approaches have been suggested for solving POMDPs by using MDP solvers in conjunction with imitation learning. MDP based POMDP solvers work well for some cases, while catastrophically failing for others. The main… CONTINUE READING

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