rulesmost
Rulesmost is a theoretical framework and software concept for constructing prioritized rule sets used in information processing and decision making. The name signals emphasis on selecting the most impactful rules for a given context. Proponents view rulesmost as a scalable alternative to exhaustive rule enumeration, aiming for broad coverage with a compact, interpretable rule set.
Core concepts include a rule base of conditional statements, an inference engine that evaluates them against
Architectures typically separate storage, context modeling, and execution. Key algorithms are rule mining from data, rule
Applications span data validation, policy enforcement, automated workflows, content moderation, and educational tools. Limitations include maintenance
Rulesmost emerged in academic and industry discussions in the 2010s as a response to the limits of