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There has been recent interest in implementing automated planning by optimizing a planning domain modeled as a stochastic system. Planning is viewed as a process where sequential decision problems are solved
in order to reach the goal, and thus, can be considered as instances of a Markov Decision Process (MDP). However, standard MDP techniques cannot solve a typical planning problem in polynomial time. Hence, the
motivation for investigating the use of quantum search techniques based on the Grover Search Algorithm, to identify policies with high utility.
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Sanjeev Naguleswaran, Langford B. White, "Quantum search in stochastic planning," Proc. SPIE 5846, Noise and Information in Nanoelectronics, Sensors, and Standards III, (23 May 2005); https://doi.org/10.1117/12.609962