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ATAL
2008
Springer

Efficient approximate inference in distributed Bayesian networks for MAS-based sensor interpretation

8 years 4 months ago
Efficient approximate inference in distributed Bayesian networks for MAS-based sensor interpretation
The multiply sectioned Bayesian network (MSBN) framework is the most studied approach for distributed Bayesian Network inference in an MAS setting. This paper describes a new framework that supports efficient approximate MASbased sensor interpretation, more autonomy and asynchrony among the agents, and more focused, situation-specific communication patterns. Its use can lead to significant improvements in agent utilization and time-to-solution. Categories and Subject Descriptors I.2.11 [Artificial Intelligence]: Distributed Artificial Intelligence General Terms Design, Performance Keywords distributed problem solving, distributed Bayesian networks
Norman Carver
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where ATAL
Authors Norman Carver
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