Simulation meta-architecture for analyzing the emergent behavior of agents

This paper describes a meta-architecture, which includes functional segments, events, and a communication link between functional segments and events. Using the object-oriented architecture systems of agents can be analyzed to determine their emergent behavior. In an agent system, each agent iteratively executes its own set of rules during its lifetime. Each agent is an individual entity with its own intelligence defined by its rule set. Rule sets for any given system can have many variations and it is not known a priori which variation will result in the most desired outcome. Since each agent is a separate entity, intelligence is distributed throughout the system, rather than existing in a centralized unit. The architecture in this paper is a framework that can be used for experimenting with variations of rule sets to assist in discovering a rule set that results in desirable system-level behavior. We also describe a case study in which the architecture is used to simulate rule sets for a group of robot agents to determine the system-level average effective speed of the robots resulting from their interactions at the individual robot level.