Approximating state estimation in multiagent settings using particle filters

@inproceedings{Doshi2005ApproximatingSE,
  title={Approximating state estimation in multiagent settings using particle filters},
  author={Prashant Doshi and Piotr J. Gmytrasiewicz},
  booktitle={AAMAS},
  year={2005}
}
State estimation consists of updating an agent's belief given executed actions and observed evidence to date. In single agent environments, the state estimation can be formalized using the Bayes filter. Exact estimation can be performed in simple cases, but approximate techniques, like particle filtering, have been used in more realistic cases. This paper extends the particle filter to multiagent settings resulting in the interactive particle filter. The main difficulty we tackle is that to… CONTINUE READING
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