Pond-Hindsight: Applying Hindsight Optimization to Partially-Observable Markov Decision Processes
Partially-observable Markov decision processes (POMDPs) are especially good at modeling real-world problems because they allow for sensor and effector uncertainty. Unfortunately, such uncertainty makes solving a POMDP computationally challenging. Traditional approaches, which are based on value iter...
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| Format: | Others |
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DigitalCommons@USU
2011
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| Online Access: | https://digitalcommons.usu.edu/etd/1035 https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=2034&context=etd |