Multi-Agent Message Filtering for Uneven Simulation Processing
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Solution Overview
Problem
Existing multi-agent simulations experience unnecessary traffic increases, leading to excessive consumption of communication resources due to messages being delivered at uniform intervals regardless of the agents' varying processing times.
Innovation Solution
A multi-agent simulation system with a center controller that adjusts message delivery frequencies based on the processing time intervals of individual agent simulators, filtering messages to reduce overall traffic and conserve resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the center controller delivers messages to all agent simulators at uniform intervals, then all agents receive updates, but traffic and communication resource consumption increase unnecessarily
Solution Approach 1:
The patent applies local quality by customizing message delivery frequency for each agent simulator based on its specific processing time interval. The center controller identifies which agents require frequent updates and which can tolerate lower frequencies, thereby optimizing communication resources while maintaining simulation reliability.
Solution Approach 2:
The system dynamically adjusts message delivery frequency for each agent simulator based on its processing capabilities. The center controller modifies the delivery interval adaptively, delivering messages more frequently to agents with shorter processing intervals and less frequently to those with longer intervals, thus resolving the contradiction between complete delivery and resource efficiency.
2Measurement precision
If messages are delivered frequently to all agent simulators, then simulation accuracy is maintained, but traffic increases and communication resources are wasted
Solution Approach 1:
The patent implements local quality by tailoring message delivery frequency to each agent simulator's processing time interval. This ensures that simulation accuracy is maintained for agents requiring frequent updates while reducing unnecessary message traffic for agents that can process information less frequently.
Solution Approach 2:
The system changes the parameter of message delivery frequency based on each agent simulator's processing characteristics. The center controller adjusts this parameter dynamically, delivering messages at optimal intervals for each agent type, thereby maintaining simulation precision while minimizing overall traffic volume.
3Ease of operation
If the center controller delivers messages at fixed intervals, then message delivery is simple, but agents with different processing speeds experience inefficiency
Solution Approach 1:
The patent applies dynamics by transitioning from fixed-interval message delivery to dynamic, adaptive intervals. The center controller adjusts message delivery timing based on each agent simulator's processing speed, ensuring that faster agents receive more frequent updates while slower agents receive updates at appropriate intervals, thereby improving overall simulation efficiency.
Solution Approach 2:
The system uses periodic action with varying periods for different agent simulators. Instead of a single fixed interval, the center controller implements multiple periodic delivery schedules tailored to each agent's processing time interval, optimizing the balance between operational simplicity and processing efficiency.
Data Source
AI summary
A multi-agent simulation system performs a simulation of a target world in which a plurality of agents interacting with each other exist. The multi-agent simulation system includes: a plurality of agent simulators configured to perform simulations of the plurality of agents, respectively; and a center controller configured to communicate with the plurality of agent simulators. The center controller performs message filtering based on a processing time interval of each agent simulator. More specifically, the center controller sets the number of the delivery message delivered per unit time to the agent simulator whose processing time interval is relatively long to be relatively small.