Optimal Continuous State POMDP Planning With Semantic Observations: A Variational Approach

Luke Burks
Luke Burks
Ian Loefgren
Ian Loefgren

arXiv: Artificial Intelligence, Volume 35, Issue 6, 2019, Pages 1488-1507.

Cited by: 1|Views6
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Abstract:

This work develops novel strategies for optimal planning with semantic observations using continuous state Partially Observable Markov Decision Processes (CPOMDPs). Two major innovations are presented in relation to Gaussian mixture (GM) CPOMDP policy approximation methods. While existing methods have many theoretically nice properties, t...More

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