Prescriptive Inductive Operations on Probabilities Serving to Decision-Making Agents
本文统一了概率分布的近似、扩展和合并等归纳操作，并阐明其使用条件，帮助决策者正确选择和运用这些工具。
Approximation, extension, and merging of probability distributions support inductive reasoning. They serve to modeling, knowledge, and preference elicitation as well as to a soft cooperation within various decision-making (DM) scenarios. The theory dubbed as the fully probabilistic design of DM strategies unifies the design of these operations on distributions. The unification decreases the danger of their improper choice and use. Still there is an uncertainty how the gained tools should be wielded. This article diminishes it by spelling out conditions ruling their exploitation. This article serves as an updated description of these tools, provides examples of their use, and guides their tailoring to diverse scenarios.