Belief Rule-Base Inference (RIMER)

Imagine a panel of experts who do not just say 'if pressure is high then failure is likely' but instead assign confidence weights across multiple failure grades simultaneously. BRB formalizes this intuition: every rule carries a belief distribution over possible outcomes rather than a single crisp conclusion. When an input arrives, all matching rules vote—weighted by their activation strengths and reliabilities—and the ER algorithm aggregates these votes into a final probabilistic verdict without losing any uncertainty information.