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CHAPTER 5. MULTI-AGENT SYSTEM
its environment, when introducing multiple agents, we will have to consider organizing the agents, and determine how the agents should interact.
In an organized multi-agent system, the agents characteristically have different capabilities and will not have global access to data in the environment, so in order to solve a common objective, they must interact. In a
multi-agent system, data is generally decentralized and execution is asynchronous, there may be little or no global control, which is why such systems are sometimes referred to as swarm systems [52, 32].
To advance individual goals and the overall system in which agents reside,
agents can communicate, coordinate and negotiate among each other.
In the following sections we will describe the widely used AEIO paradigm
and BDI agent architecture.
5.4
The AEIO paradigm
A multi-agent system can be decomposed into four main entities: Agent,
Environment, Interaction and Organization, which is referred to as the AEIO
paradigm [32], which contains the following three statements, from which
we will describe the declarative principle.
The Declarative Principle
MAS = A + E + I + O
The Functional Principle
P
Function(MAS) = Function(entities) + Emergence Function
The Recursive Principle
Entity = basic entity I MAS
The declarative principle is composed of the following four components:
1. Agent: The agent is the basic component in a multi-agent system,
which we described in section 5.1.
2. Environment: The environment, which was described in section 5.2,
is where agents evolve, and can be either virtually or physically modeled according to whether one chooses software or hardware agents.