2013/01/16 by Dennis K. Nilsson, Dennis Nilsson, Steffen L. Lauritzen +2
Computer Science · #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #cs.AI
paper · pdf · doi:10.48550/arxiv.1301.3881
Appears in Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI2000)
arxiv created 2013/01/16 · openalex publication_date 2013/01/16 · arxiv updated 2013/01/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present a new approach to the solution of decision problems formulated as influence diagrams. The approach converts the influence diagram into a simpler structure, the LImited Memory Influence Diagram (LIMID), where only the requisite information for the computation of optimal policies is depicted. Because the requisite information is explicitly represented in the diagram, the evaluation procedure can take advantage of it. In this paper we show how to convert an influence diagram to a LIMID and describe the procedure for finding an optimal strategy. Our approach can yield significant savings of memory and computational time when compared to traditional methods.