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Corrado Grappiolo, Shimon Whiteson, Gregor Pavlin, and Bram Bakker. Integrating Distributed Bayesian Inference and Reinforcement Learning for Sensor Management. In FUSION 2009: Proceedings of the Twelfth International Conference on Information Fusion, pp. 93–101, July 2009.
This paper introduces a sensor management approach that integrates distributed Bayesian inference (DBI) and reinforcement learning (RL). DBI is implemented using distributed perception networks (DPNs), a multiagent approach to performing efficient inference, while RL is used to automatically discover a mapping from the beliefs generated by the DPNs to the actions that enable active sensors to gather the most useful observations. The resulting method is evaluated on a simulation of a chemical leak localization task and the results demonstrate 1) that the integrated approach can learn policies that perform effective sensor management, 2) that inference based on a correct observation model, which the DPNs make feasible, is critical to performance, and 3) that the system scales to larger versions of the task.
@InProceedings{grappiolo:fusion09,
author = "Corrado Grappiolo and Shimon Whiteson and Gregor Pavlin and Bram Bakker",
title = "Integrating Distributed {B}ayesian Inference and Reinforcement Learning for Sensor Management",
booktitle = "FUSION 2009: Proceedings of the Twelfth International Conference on Information Fusion",
month = "July",
pages = "93-101",
year = 2009,
}
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