Systematic Generation of Risk Evaluation Systems basedon Temporal Motivational Theory
2016 (English)In: USB Proceedings of the 13th Workshop on Modeling Decisions for Artifical Intelligence (MDAI2016) / [ed] Vicenc Torra, 2016, 122-132 p.Conference paper (Refereed)
This paper provides a schematic, systematic and structured approach todeveloping Bayesian belief networks to assess risks in contexts dened by activities.The method ameliorates elicitation, specication and validation of expert knowledgeby reusing a schematic structures based on reasoning of risks based on the temporal motivationaltheory. The method is based on earlier work that took a rst signicant steptowards reducing the complexity of development of Bayesian belief networks by clusteringand classifying variables in Bayesian belief networks as well as associating the processwith human deciions making. It may be possible to reduce the role of a facilitiatoror even remove the facilitator altogether by using this method. The method is partiallyvalidated and further work is required on this topic.
Place, publisher, year, edition, pages
2016. 122-132 p.
Bayesian belief networks, elicitation, specication, validation, temporal motivational theory
Research subject Technology
IdentifiersURN: urn:nbn:se:his:diva-12941ISBN: 978-99920-3-099-8OAI: oai:DiVA.org:his-12941DiVA: diva2:972644
Modeling Decisions for Artificial Intelligence