Simulation Causal Analysis for Spatial Design Evaluation
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Solution Overview
Problem
Existing behavior simulation methods struggle to provide clear reasons for evaluation results, requiring extensive knowledge of the target space and leading to high computational burdens due to numerous spatial design trials.
Innovation Solution
An information processing apparatus that analyzes agent-based simulation results to detect causal relationships among attributes, identifying cause attributes for a target evaluation and outputting information for improving spatial designs with reduced computational effort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If extensive knowledge of the target space is required to interpret simulation results, then evaluation accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The patent introduces an automated causal analysis system that acts as an intermediary between simulation results and human interpreters. The system automatically detects causal relationships among simulation attributes and generates human-readable explanations, eliminating the need for users to possess extensive domain knowledge while maintaining evaluation accuracy.
2Manufacturing precision
If numerous spatial design trials are conducted to find optimal designs, then manufacturing precision is improved, but productivity deteriorates
Solution Approach 1:
The patent performs preliminary causal analysis on simulation attributes before conducting numerous design trials. By pre-identifying which attributes causally influence evaluation outcomes, the system can focus subsequent trials on only the critical factors, dramatically reducing the number of trials needed while maintaining design optimization accuracy.
Solution Approach 2:
The patent extracts and identifies the critical causal attributes from the full set of simulation attributes. By separating the essential causal factors from non-essential ones, the system enables focused optimization trials that achieve the same design quality with fewer iterations.
3Measurement precision
If comprehensive simulation analysis is performed to identify all causal relationships, then measurement precision is improved, but device complexity deteriorates
Solution Approach 1:
The patent segments the complex causal analysis task into distinct modular components: attribute extraction, relationship detection, and result generation. Each module handles a specific aspect of the analysis independently, making the overall system more manageable and maintainable while achieving comprehensive causal relationship detection.
Data Source
AI summary
A computer obtains simulation result data including a plurality of records corresponding to a plurality of agents that act within a designated space, each of the plurality of records including attribute values of a plurality of attributes concerning an action result of one agent among the plurality of agents. Based on the simulation result data, the computer detects one or more causal relationships among the plurality of attributes, each causal relationship indicating that one attribute is a cause of another attribute. Based on the one or more causal relationships, the computer determines, among the plurality of attributes, a cause attribute that indicates a cause for a target attribute indicating an evaluation of the space. The computer outputs information corresponding to the cause attribute.