Decisions, Graphs, and Artificial Reasoning for Uncertainty of Information

A decision is a conclusion reached after considering information, while decision making is the process of making choices after assessing alternatives with the information gathered. Most decisions made lead to an action or a choice. However, this process is often interactive and iterative in nature. Interaction can be from people, agents, or both. The interaction can take the form of additional data, different criteria, and changes to the goals for the decision. A single decision may not be the final decision but made at a single point that flows into another. Thus, iterations can initiate this flow of decisions at various points and in a cycle. In the decision cycle the decision may be repeated, as fine tuning of the system or tasks occur. Then there is the ongoing challenge that decisions nor the decision making process is simple nor is it perfect. Many techniques strive to capture the uncertainty that this imperfection creates. In this work we are referencing continued research being conducted under Artificial Reasoning for Uncertainty of Information (UoI). UoI is a reason based approach that builds on the concept of imperfect information. The objective of the UoI research is to represent and present the reasons, causes for specified uncertainty for a task, specifically the decisions for the task. As the UoI research expands to ideally allow greater adaptability, the area of graphs is being explored. Graphs are a decision making tool where connections between inputs (information, criteria, goals, etc.) and outputs (alternatives, choices,.) can be shown and analyzed. Utilizing graphs is also helpful as new capabilities are integrated into the UoI concept. This paper will explore how graphs are and can be used to incorporate new features and new capabilities particularly for selected warfighter functions.