Color-Coded Visual Comparison of Decision Logic Structures
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Solution Overview
Problem
Existing decision logic representation methods, such as decision trees, directed acyclic graphs, and exception-based directed acyclic graphs, face challenges in efficiently comparing and visualizing complex decision strategies, particularly when dealing with hundreds of variables and outcomes, leading to difficulties in displaying and analyzing large numbers of nodes.
Innovation Solution
The technique involves converting strategies into logically equivalent read-once, leveled decision logic structures, such as directed acyclic graphs or exception-based directed acyclic graphs, allowing for visual comparison by displaying differences and similarities through color-coded representations, and generating cross pair graphs to highlight behavioral and structural differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If decision trees are used to represent complex decision logic involving hundreds of variables, then the decision logic can be comprehensively represented, but the number of nodes increases making it difficult to display and analyze
Solution Approach 1:
The patent segments the complex decision logic into multiple sub-strategies or sub-trees, each handling a specific portion of the overall decision-making process. This allows the system to manage hundreds of variables by dividing them into manageable groups, reducing the cognitive load and visual complexity while maintaining comprehensive representation capability.
Solution Approach 2:
The patent introduces hierarchical organization as an additional dimension to represent decision logic. Instead of presenting all nodes at a single level, the system organizes nodes across multiple hierarchical levels, allowing users to navigate from high-level strategic decisions down to specific variable evaluations. This dimensional transformation reduces the apparent complexity by distributing nodes across vertical hierarchy rather than horizontal expansion.
2Measurement precision
If the number of nodes in decision logic structures increases to handle hundreds of variables, then more comprehensive decisions can be made, but displaying and analyzing these structures becomes difficult
Solution Approach 1:
The patent performs preliminary organization and structuring of decision logic nodes before presentation to users. By pre-grouping related nodes, establishing hierarchical relationships, and organizing variables into logical categories beforehand, the system prepares the complex structure in advance to facilitate easier display and analysis. This preliminary structuring reduces the immediate cognitive burden when users encounter the full decision logic.
Solution Approach 2:
The patent introduces intermediate organizational structures such as strategy groups, variable categories, and hierarchical levels that act as mediators between the raw complex decision logic and the user interface. These intermediary structures aggregate and organize numerous individual nodes into meaningful groups, making the overall structure more manageable for display and analysis while preserving the detailed evaluation precision.
3Reliability
If traditional decision tree structures are used, then decision logic can be represented, but comparing and visualizing differences between strategies becomes challenging
Solution Approach 1:
The patent creates standardized copies or representations of decision logic structures that can be systematically compared. By generating normalized versions of different strategies with consistent formatting and organization, the system enables effective comparison while preserving the unique logical relationships and decision pathways of each strategy. This copying approach maintains accuracy while facilitating visual differentiation.
Solution Approach 2:
The patent employs color-coding to visually distinguish different strategies, decision paths, and node types during comparison. By assigning color identifiers to corresponding nodes across different decision trees and using color gradients to indicate similarities and differences, the system enhances visualization of structural and behavioral variations without losing the underlying logical accuracy of each strategy.
Data Source
AI summary
A request to compare strategies is received. The first strategy can be graphically represented by a first set of linked nodes arranged in a first form of decision logic. The second strategy can be graphically represented by a second set of linked nodes arranged in a second form of decision logic. The first set of linked nodes can be converted to a first modified set of linked nodes arranged in a third form of decision logic. The second set of linked nodes can be converted to a second modified set of linked nodes arranged in the third form of decision logic. A color-coded visual representation of the first modified set of linked nodes and the second modified set of linked nodes can be provided to a user. Related apparatus, techniques, and articles are also described.