Automated Decision Matrix Generation Using Generative Transformers
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Solution Overview
Problem
Existing decision-making technologies lack automation in model-based workflows, making it difficult for users to efficiently evaluate options based on multiple criteria, especially in complex decision domains.
Innovation Solution
A method that utilizes a generative pre-trained transformer model to automate the decision-making process by generating scores for options based on user input, factors, and context data, and presenting the results in a decision matrix.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual decision-making processes are used, then users can evaluate options based on multiple criteria, but the process is time-consuming and lacks efficiency
Solution Approach 1:
The system enables automated self-service decision-making by using the generative pre-trained transformer model to automatically evaluate options against multiple criteria and factors. The model autonomously generates scores and composite scores without requiring manual intervention, thereby improving productivity while reducing time loss.
Solution Approach 2:
The patent replaces manual mechanical decision-making processes with an automated computational system. The generative pre-trained transformer model substitutes human manual evaluation with automated scoring mechanisms, generating decision matrices efficiently and reducing the time required for option evaluation.
2Measurement precision
If comprehensive evaluation of multiple options and factors is performed, then decision accuracy improves, but the complexity of the process increases
Solution Approach 1:
The system segments the complex decision-making process into distinct components: individual factor evaluations, option scoring, and composite score calculation. The generative pre-trained transformer model processes each option-factor combination separately, maintaining measurement precision while managing complexity through structured segmentation of the evaluation workflow.
Solution Approach 2:
The generative pre-trained transformer model serves multiple functions within the decision-making system: it evaluates individual factors, generates scores for each option-factor combination, calculates composite scores, and produces the decision matrix. This multi-functionality maintains comprehensive evaluation accuracy while reducing overall process complexity by consolidating multiple tasks into a single versatile model.
Data Source
AI summary
A method for a decision-making workflow includes: receiving a prompt associated with a pending decision; identifying a set of options representing candidates for the pending decision; and identifying a set of factors representing attributes of the set of options. The method further includes, generating a script instructing a generative transformer model to, based on the prompt: access a set of combinations of options and factors based on the set of options and the set of factors; and generate a score, in a set of scores, for each combination in the set of combinations, the score representing suitability of the combination according to pending decision. The method also includes: calculating a composite score, in a set of composite scores, for each option, in the set of options based on the set of scores; and generating a decision matrix including cells containing the set of scores and the set of composite scores.