Simulation Continuity via Checkpoint Resumption
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Solution Overview
Problem
Networked video games face challenges in testing non-player character (NPC) behavior due to difficulties in simulating real-world network conditions and coordinating end user devices, making it hard to assess NPC suitability and debug software or hardware components without actual gameplay data.
Innovation Solution
A system and method that simulate NPC gameplay across networked end user devices by identifying available devices with spare computing capacity, using a test game engine to interact with NPCs, and providing NPC specifications to execute simulated gameplay sessions, allowing for real-world condition testing and data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a simulation is running on networked end user devices and a processing resource goes offline, then the simulation cannot continue without interruption, but restarting the simulation causes loss of simulation state and wasted computational resources
Solution Approach 1:
The system performs preliminary actions by pre-computing and storing simulation state checkpoints before processing resources go offline. When a resource becomes unavailable, the simulation can resume from the most recent checkpoint rather than restarting, preventing loss of simulation state and computational waste.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring the availability of processing resources and automatically adjusting simulation execution. When resources go offline, the system detects this condition and triggers state recovery procedures to maintain simulation continuity without manual intervention.
2Reliability
If simulation state is frequently saved to ensure continuity, then simulation can resume after resource failure, but system storage requirements and computational overhead increase
Solution Approach 1:
The system applies local quality by saving simulation state selectively at specific checkpoints rather than continuously. State is saved at predetermined intervals or at critical simulation events, reducing overall storage requirements while maintaining the ability to resume simulations after resource failures.
Solution Approach 2:
The system uses partial action by saving only the essential simulation state data required for resumption rather than complete simulation data. This selective state saving reduces storage overhead while providing sufficient information to continue the simulation from the checkpoint.
Data Source
AI summary
A system and method is provided that simulates gameplay of non-player characters (NPCs) distributed across networked end user devices. The system may identify end user devices that are connected to the system through a network and are available to participate in a simulation in which each participating end user device is provided with one or more NPCs to be executed. An end user device may be available to participate when it has sufficient computing capacity, such as when in an idle or standby state. As such, the system may leverage spare computing capacity of networked end user devices to execute NPCs at networked end user devices during a simulation. In this manner, the behavior of an NPC may be tested using real-world conditions that may affect gameplay, such as a network connection quality, user-to-user game engine coordination and data exchanges, and/or other real-world conditions associated with networked end user devices.