Decision Making Using Rough Set based Spanning Sets for a Decision System

TL;DR

This paper introduces a novel decision-making approach using Rough Set based spanning sets for decision tables, enabling automatic decision class learning and aiding experts in complex, time-sensitive scenarios.

Contribution

It proposes a new concept of span for decision tables in Rough Set theory, focusing on automating decision class determination for practical applications.

Findings

Successfully applied to flood relief and rescue team assignment.

Automates decision class learning, reducing manual effort.

Enhances decision-making in uncertain, real-world situations.

Abstract

Rough Set based concepts of Span and Spanning Sets were recently proposed to deal with uncertainties in data. Here, this paper, presents novel concepts for generic decision-making process using Rough Set based span for a decision table. Majority of problems in Artificial Intelligence deal with decision making. This paper provides real life applications of proposed Rough Set based span for decision tables. Here, novel concept of span for a decision table is proposed, illustrated with real life example of flood relief and rescue team assignment. Its uses, applications and properties are explored. The key contribution of paper is primarily to study decision making using Rough Set based Span for a decision tables, as against an information system in prior works. Here, the main contribution is that decision classes are automatically learned by the technique of Rough Set based span, for a particular problem, hence automating the decision-making process. These decision-making tools based on span can guide an expert in taking decisions in tough and time-bound situations.