Multi-Agent System
The widespread use of distributed information services will radically
alter the way in which both organizations and individuals work.
There are many indicators of this coming information revolution.
Though there exists no generally accepted definition, an agent can
be thought of as an entity with domain knowledge, goals and actions.
An autonomous agent is capable of interacting independently and
effectively with its sensors and effectors in order to achieve specified or
self-sired goals.
Russell and Norvig define an agent as: Anything that can be
viewed as perceiving its environment through
sensors and acting upon that environment through effectors.
The study of autonomous agent behaviors, the way in
which an autonomous agent acts, is advancing rapidly as a sub-field of
distributed artificial intelligence (DAI). Creating an intelligent
autonomous agent to the level of human performance is one of the dreams
of AI researchers.
Multi-agent systems deal with the construction of complex systems
involving multiple agents and their coordination. It inherits from the
distributed AI. Distributed AI (DAI) systems are
not capable of emergent contexts and changing problem-solving roles for
concerned agents.
A multi-agent system (MAS) is a distributed computing system with
autonomous interacting intelligent agents that coordinate their actions
so as to achieve its goal(s) jointly or competitively. The agents in a
multi-agent scenario, may have homogeneous or heterogeneous structures.
In a homogeneous MAS, all of the agents have identical structure (goals,
domain knowledge, and set of actions). They may differ by way of their
sensor input and effector output. In a heterogeneous situation, agents
can have different goals, domain knowledge and actions. The agents in
such a system may be friendly (benevolent) or may be inhibiting each
other (competitive). The agents, situated differently in the
environment, receive different sensory inputs and initiates different
actions. Heterogeneity imparts much power to the MAS at the cost of
complexity.
Multi-agent systems: A survey from the robot soccer perspective.
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