Reusable influence diagrams.
Influence Diagrams have been recognized as a suitable formalism for building probabilistic expert systems. Nevertheless, the most part of applications consists in stand-alone systems, concerning a very limited domain. On the other hand, Artificial Intelligence research has outlined Blackboard Architectures as the basis for building expert systems in which several knowledge sources, in general built with different formalisms, cooperate to the solution of a complex task. This paper addresses the use of influence diagrams as knowledge sources of such a system, and particularly faces the problem of reusing the same influence diagram in different inference phases. We will show that, specially in planning tasks, the modularity requirement of keeping the knowledge sources separated, may imply that an influence diagram must call another influence diagram to solve itself and to maintain the coherence of the whole set of decisions underlying the plan. Conditions for the correctness of this concatenation of knowledge sources will be provided, and an example from the medical domain of therapy planning for Acute Myeloid Leukemia will be shown, as an implemented prototype exploiting these ideas.
Dipartimento di Informatica e Sistemistica, Università di Pavia, Italy.
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Bellazzi
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Quaglini
D000208:Acute Disease; D000293:Adolescent; D000367:Age Factors; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000009:adverse effects / Q000097:blood / Q000627:therapeutic use; D001185:Artificial Intelligence; D001499:Bayes Theorem; D016026:Bone Marrow Transplantation; D002648:Child; D016572:Cyclosporine / Q000008:administration & dosage / Q000009:adverse effects / Q000097:blood; D003661:Decision Support Techniques; D005103:Expert Systems; D006086:Graft vs Host Disease / Q000209:etiology / Q000517:prevention & control; D006801:Humans; D007951:Leukemia, Myeloid / Q000188:drug therapy / Q000628:therapy; D008727:Methotrexate / Q000008:administration & dosage / Q000009:adverse effects / Q000097:blood; D008954:Models, Biological; D016571:Neural Networks, Computer; D010347:Patient Care Planning; D011379:Prognosis; D012737:Sex Factors; D018511:Systems Integration
D016572:Cyclosporine; D008727:Methotrexate