Simulated Human Interaction Model for Variable Control
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Solution Overview
Problem
Investigating interactions between humans is challenging due to limitations in conducting real-life experiments, such as limited participant availability and difficulty in controlling personal and environmental variables.
Innovation Solution
A system and method that utilize simulated humans, where a processor builds models of human behavior and tasks, trains them on datasets of human interactions, and allows for adjustment of parameters to control and investigate personality and environmental variables during simulated interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-life experiments with human participants are conducted, then actual human interaction data is obtained, but participant availability is limited and personal/environmental variables cannot be fully controlled
Solution Approach 1:
The patent creates simulated human agents that copy and replicate human behavior patterns, personality traits, and interaction dynamics. These digital twins allow researchers to conduct numerous controlled experiments without relying on physical human participants, thereby increasing productivity while maintaining reliability through parameter control.
Solution Approach 2:
The system enables independent adjustment of personality parameters, environmental conditions, and task variables in simulated interactions. This allows researchers to systematically vary parameters across multiple experiments to study their effects on interaction outcomes, achieving both high productivity and reliable control that is impossible with real human subjects.
2Quantity of substance
If more experiments are conducted with real participants, then more data is collected, but participant availability and experimental control are compromised
Solution Approach 1:
By creating multiple simulated human agents with diverse personality profiles and behavior patterns, the system can generate large volumes of interaction data through automated simulations. This eliminates the need to recruit and coordinate numerous real participants, making the experimental process much easier to operate and scale.
Solution Approach 2:
The simulated agents autonomously engage in interactions based on their programmed personality traits and behavioral models, eliminating the need for human operators to manually conduct each experiment. The system self-generates interaction data through automated simulations, significantly reducing operational complexity.
3Measurement precision
If real human interactions are observed, then authentic behavior is captured, but it is difficult to isolate and investigate specific personality or environmental variables
Solution Approach 1:
The system allows independent manipulation of personality parameters (e.g., extraversion, neuroticism) and environmental variables (e.g., task type, group size) in simulated interactions. Researchers can systematically vary one parameter at a time while holding others constant, enabling precise measurement of individual variable effects with complete flexibility to investigate any combination of variables.
Solution Approach 2:
The patent decomposes human personality and behavior into discrete, adjustable parameters that can be independently controlled and measured. This segmentation allows researchers to isolate specific personality traits or environmental factors and investigate their individual contributions to interaction outcomes, achieving measurement precision that is impossible in uncontrolled real-world settings.
Data Source
AI summary
A system includes a processor configured to build a model of human behavior that can be assigned to a simulated human, where the model is trained on a dataset of interactions between humans, and parameters of the model can be adjusted. The processor is further configured to build a model of a task to be engaged in by a plurality of simulated humans, simulate interactions between the plurality of simulated humans, and display behavior of the simulated humans and information about the interactions between the simulated humans during simulated interactions.