Unlike the lower two layers, the top layer of reasoning is specifically targeted at reasoning on a deep level of knowledge which is generally model specific and often symbolic in nature. The functionality of the top layer needs to support three different types of capabilities.
• Probabilistic reasoning - Calculates probabilities in order to make predictions or decisions based on otherwise uncertain or insufficient information.
• Decision support - Evaluates the relative merits of alternative decisions or courses of action.
• Behavior simulation - utilizes models and rules to identify a behavioral directive to respond to a recognized situation. In the case where more than one behavior might be appropriate, the framework needs to be able to identify which one is optimal for a given criteria.
The examples of uncertainty present in the top layer include irrelevance, stochastic variance, parametric errors, and modeling problems.
