Multi-Agent Simulation Speed Control via Remainder Time Rate
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Solution Overview
Problem
Multi-agent simulation systems face challenges in maintaining accuracy and speed due to variations in computing and networking environments, leading to either overly fast simulations that reduce accuracy or slow simulations that waste resources.
Innovation Solution
A multi-agent simulation system with a center controller that adjusts the speed ratio of the target world's time flow based on an index value calculated by agent simulators, optimizing the simulation speed by accelerating it when there is a margin and decelerating it when necessary to maintain accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the simulation speed is increased to proceed faster than real time, then productivity is improved, but manufacturing precision deteriorates due to messages not arriving within processing timing
Solution Approach 1:
The system dynamically adjusts the speed ratio based on the calculated index value (remainder time rate). When the index value indicates sufficient margin (remainder time rate ≥ first threshold), the speed ratio is increased to accelerate simulation. When the index value indicates insufficient margin (remainder time rate ≤ second threshold), the speed ratio is decreased to maintain accuracy. This dynamic adjustment resolves the contradiction by adapting simulation speed to real-time computational conditions.
Solution Approach 2:
Each agent simulator calculates an index value representing the remainder time rate and feeds this information back to the center controller. The center controller uses this feedback to adjust the speed ratio, creating a closed-loop control system that balances simulation speed and accuracy based on actual computational performance and message delivery timing.
2Manufacturing precision
If the simulation speed is decreased to ensure messages arrive within processing timing, then manufacturing precision is improved, but productivity deteriorates due to increased waiting time
Solution Approach 1:
The system avoids static slow simulation by dynamically adjusting speed ratio. When computational environment is good and messages arrive timely, the speed ratio is increased to maximize productivity. When computational environment is poor, the speed ratio is decreased to maintain precision. This eliminates unnecessary waiting time while preserving accuracy when needed.
Solution Approach 2:
The system changes the speed ratio parameter based on the index value (remainder time rate). By adjusting this parameter dynamically rather than using a fixed slow speed, the system achieves high productivity when conditions permit while maintaining precision when conditions require it, resolving the contradiction between speed and accuracy.
3Productivity
If the speed ratio is increased without considering computational environment, then productivity is improved, but reliability deteriorates due to processing time exceeding time granularity
Solution Approach 1:
The index value calculation and feedback mechanism monitors whether processing time is sufficient relative to time granularity. The center controller uses this feedback to adjust speed ratio, ensuring processing reliability is maintained while maximizing productivity. The system only increases speed when the index value confirms sufficient computational margin.
Solution Approach 2:
The system performs preliminary calculation of the index value (remainder time rate) before adjusting speed ratio. This preliminary assessment ensures that speed increases are only made when computational environment can reliably support the faster processing, preventing reliability deterioration before it occurs.
Data Source
AI summary
The multi-agent simulation system includes a plurality of agent simulators provided for each of the plurality of agents and a center controller. The plurality of agent simulators are programmed to simulate a state of each of the plurality of agents while causing the plurality of agents to interact with each other by exchanging messages. The center controller is programmed to control a speed ratio of a flow of time in the target world to a flow of time in a real world. Each of the plurality of agent simulators calculates an index value corresponding to a remainder time rate. The remainder time rate is a rate of a remainder time to an update time interval for updating a state of a target agent to be simulated. The center controller controls the speed ratio based on the index value calculated by each of the plurality of agent simulators.