A Knowledge Acquisition Tool for Bayesian-Network Troubleshooters
This addresses the knowledge acquisition bottleneck for domain experts using Bayesian networks in troubleshooting, but it is incremental as it builds on existing methods.
The paper tackles the problem of knowledge acquisition for Bayesian-network troubleshooters by introducing a domain-specific tool that allows domain experts to specify troubleshooting information intuitively without requiring Bayesian network knowledge, efficiently removing the traditional bottleneck.
This paper describes a domain-specific knowledge acquisition tool for intelligent automated troubleshooters based on Bayesian networks. No Bayesian network knowledge is required to use the tool, and troubleshooting information can be specified as natural and intuitive as possible. Probabilities can be specified in the direction that is most natural to the domain expert. Thus, the knowledge acquisition efficiently removes the traditional knowledge acquisition bottleneck of Bayesian networks.