Space-Efficient Inference in Dynamic Probabilistic Networks

  title={Space-Efficient Inference in Dynamic Probabilistic Networks},
  author={John Binder and Kevin P. Murphy and Stuart J. Russell},
Dynamic probabilistic networks (DPNs) are a useful tool for modeling complex stochastic processes. The simplest inference task in DPNs is monitoring | that is, computing a posterior distribution for the state variables at each time step given all observations up to that time. Recursive, constant-space algorithms are well-known for monitoring in DPNs and other models. This paper is concerned with hind-sight | that is, computing a posterior distribution given both past and future observations… CONTINUE READING
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