Abductive inference in Bayesian networks using distributed overlapping swarm intelligence

@article{Fortier2015AbductiveII,
  title={Abductive inference in Bayesian networks using distributed overlapping swarm intelligence},
  author={Nathan Fortier and John W. Sheppard and Shane Strasser},
  journal={Soft Comput.},
  year={2015},
  volume={19},
  pages={981-1001}
}
In this paper we propose several approximation algorithms for the problems of full and partial abductive inference in Bayesian belief networks. Full abductive inference is the problem of finding the k most probable state assignments to all non-evidence variables in the network while partial abductive inference is the problem of finding the k most probable state assignments for a subset of the nonevidence variables in the network, called the explanation set. We developed several multi-swarm… CONTINUE READING
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