A Hybrid Genetic/Optimization Algorithm for Finite-Horizon, Partially Observed Markov Decision Processes

@article{Lin2004AHG,
  title={A Hybrid Genetic/Optimization Algorithm for Finite-Horizon, Partially Observed Markov Decision Processes},
  author={Zong-Zhi Lin and James C. Bean and Chelsea C. White},
  journal={INFORMS Journal on Computing},
  year={2004},
  volume={16},
  pages={27-38}
}
The partially observed Markov decision process (POMDP) is a generalization of a Markov decision process that allows for noise corrupted and costly observations of the underlying system state. The value function of the finite horizon POMDP is known to be piecewise affine and convex in the probability mass vector over the state space. Such a function can be represented by a finite set of affine functions. In this paper, we develop and evaluate an exact algorithm, GAMIP, which integrates a genetic… CONTINUE READING
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