Believing in POMDPs

نویسندگان

  • Felix Richter
  • Thomas Geier
  • Susanne Biundo-Stephan
چکیده

Partially observable Markov decision processes (POMDP) are well-suited for realizing sequential decision making capabilities that respect uncertainty in Companion systems that are to naturally interact with and assist human users. Unfortunately, their complexity prohibits modeling the entire Companion system as a POMDP. We therefore propose an approach that makes use of abstraction to enable employing POMDPs in Companion systems and discuss challenges for applying it.

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تاریخ انتشار 2015