Optimal continuous state POMDP planning with semantic observations

Luke Burks
Luke Burks

CDC, pp. 1509-1516, 2017.

Cited by: 3|Views2
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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). We propose two major innovations to Gaussian mixture (GM) CPOMDP policy approximation methods. While these state of the art methods have many theoretically nice properties, th...More

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