Loading content
Multi-agent systems describe distributed collections of autonomous, interacting agents that cooperate or compete to solve complex tasks. They provide architectural principles for coordination, negotiation, and emergent behavior across software or robotic agents. MAS apply in simulation, automation, distributed control and socio-technical modeling.
Use this profile to understand the building block briefly, place it in the model, and switch to the 360° assessment when needed.
A multi-agent system consists of autonomous agents that perceive, act, and interact in a shared environment.
Multi-agent systems emerged at the intersection of AI, distributed AI, and distributed systems; FIPA formalized communication and interaction models.
Imagine independent actors with local information whose interactions produce system-level behavior.
An agent perceives states and chooses actions.
The environment provides shared context and responds to actions.
Interaction may be communication, cooperation, or competition.
MAS make distributed domains modelable, but require tests for emergent behavior, communication, and conflicts between local goals.
Where this building block is located in the topic model.
Explore how this building block connects to concepts, methods, technologies, and tools.
These sources establish the term and its professional meaning.
All direct connections of the current building block in a compact text view.
This classification shows where the building block typically matters, how demanding it is, and what kind of impact it has in the model.
The level within the organization (enterprise, domain, team) at which the AssetBlock is applied.