Constraint-Based Scenario Definition for Immersive Training
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Solution Overview
Problem
Current scenario definition languages fail to clearly define linkages between scenario events and training objectives, limiting flexibility and effectiveness in sequencing, scheduling, and monitoring of immersive scenarios such as military exercises and computer-based games.
Innovation Solution
The PRESTO system employs a pedagogically sound scenario definition language, scenario authoring tools, and decision support tools that utilize constraint programming to relax scenario specifics, allowing for flexible sequencing and scheduling of conditions, and provides real-time monitoring and corrective guidance during scenario execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If current scenario definition languages are used to provide high fidelity detail, then scenario realism is improved, but the linkage between scenario events and training objectives becomes unclear
Solution Approach 1:
The scenario definition is segmented into distinct components: training objectives, conditions, events, and constraints. Each component is separately defined and linked through explicit relationships, allowing high-fidelity scenario detail while maintaining clear connections to training objectives through the structured framework.
Solution Approach 2:
The patent introduces an intermediary framework that connects scenario events to training objectives through defined conditions and constraints. This intermediary structure acts as a bridge, ensuring that detailed scenario elements remain linked to their pedagogical purposes through explicit relationships.
2Reliability
If scenario conditions are strictly defined and scripted, then scenario control is improved, but flexibility in sequencing and scheduling is reduced
Solution Approach 1:
The scenario framework transitions from static scripting to dynamic condition-based control. Conditions are defined with constraints that allow multiple valid sequences and timings, enabling the scenario to adapt dynamically while maintaining control through constraint satisfaction rather than rigid scripting.
Solution Approach 2:
The patent changes parameters from fixed script values to constraint-based ranges. Instead of specifying exact times and sequences, the framework uses parameter ranges and constraints that define acceptable variations, providing both control and flexibility simultaneously.
3Measurement precision
If detailed scripting is used for each scenario event, then event precision is improved, but complexity of scenario management increases
Solution Approach 1:
The patent extracts the essential elements from detailed event scripting and places them into a structured framework of objectives, conditions, and constraints. This extraction reduces management complexity by focusing on key elements while maintaining precision through the formal constraint-based representation.
Solution Approach 2:
The framework provides universal structures and templates that can be applied across different scenario types. By using standardized condition and constraint definitions, the system reduces management complexity through reusability while maintaining event precision through consistent formal representations.
4Stability of the object's composition
If scenario events are sequentially scripted, then narrative coherence is improved, but adaptability to unexpected events is reduced
Solution Approach 1:
The framework enables dynamic scenario execution where the narrative coherence is maintained through constraint satisfaction rather than fixed sequencing. When unexpected events occur, the system can dynamically adjust the scenario path while ensuring all training objectives and conditions are ultimately satisfied, preserving narrative coherence through the constraint framework.
Solution Approach 2:
The patent incorporates feedback mechanisms that monitor condition satisfaction during scenario execution. This feedback allows the system to detect when unexpected events occur and adjust the scenario accordingly, maintaining narrative coherence by ensuring that all constraints and training objectives are still met through alternative paths.
Data Source
AI summary
Systems and methods to define a scenario of conditions comprising the steps of defining at least one condition for at least one educational objective, the at least one condition being represented by a constraint and scheduling the conditions into a scenario of conditions. In some embodiments, the scheduling is performed by analyzing the constraints using constraint programming. In some embodiments, the constraints comprise mathematical or computational constraints representing a range of variables. Also disclosed are systems and methods to monitor a scenario of conditions.