0.5 0.5 C_a 0.5 0.5 0.5 0.5 C_a 0.5 0.5 0.5 0.5 C_b 0.5 0.5 0.5 0.5 C_b 0.5 0.5 0.5 0.5 Figure 7.3: Conditional independence in an influence diagram. In these influence diagrams, A and B are conditionally independent given C. As shown, the conditioning event can be either (a) a chance event or (b) a decision (note that node IDs are indexed as GeNIe requires unique node identifiers; choose View/Node/ByName to see the names).\nReference:\nRobert T. Clemen, Making Hard Decisions: An Introduction to Decision Analysis, Second Edition. Duxbury Press, 1996. C 100 62 140 98 A 61 122 99 158 B 141 122 180 158 C 261 62 299 98 B 301 122 340 158 A 220 122 261 158 Figure 7.3: Conditional independence in an influence diagram. In these influence diagrams, A and B are conditionally independent given C. As shown, the conditioning event can be either (a) a chance event or (b) a decision (note that node IDs are indexed as GeNIe requires unique node identifiers; choose View/Node/ByName to see the names).\nRobert T. Clemen, Making Hard Decisions: An Introduction to Decision Analysis, Second Edition. Duxbury Press, 1996. 22 180 513 332 a 117 28 126 47 b 269 28 279 47