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

• Type: Conference
• Year: 2008
• Where: ATAL
• Authors: Norman Carver
• Keywords: ATAL 2008, Bayesian Network Inference, Bayesian Networks, Distributed Artificial Intelligence, Intelligent Agents