intelligent agent and muti-agents systems

Smart Agents

Multi-agent system

Computerized system composed of multiple interacting

intelligent agents within an environment.

Intelligent agent

autonomous entity which observes through sensors and acts

upon an environment using actuators

Intelligent agents may also learn or use knowledge to

achieve their goals.

Can be used to solve problems that are difficult or

impossible for an individual agent or a monolithic system to solve.

Classes

Classes

Simple reflex agents

Simple reflex agents act only on the basis of the current percept.

Model-based reflex agents

A model-based agent can handle partially observable environments. Its current state is stored inside the agent maintaining some kind of structure which describes the part of the world which cannot be seen.

Goal-based agents

It is more flexible because the knowledge that supports its

decisions is represented explicitly and can be modified.

Utility-based agents

Goal-based agents only distinguish between goal states and non-goal states. It is possible to define a measure of how desirable a particular state is.

Learning

agents

The most important distinction is between the "learning element", which is responsible for making improvements, and the "performance element", which is responsible for selecting external actions.

Other

classes of intelligent agents

Decision Agents

Input Agents

Processing Agents

Spatial Agents

World Agents

Believable agents

Physical Agents

Temporal Agents

based

The agent function is based on the condition-action rule: if condition then action.

Characteristics

Autonomy

The agents are at least partially independent, self-aware,

autonomous

Local

views

No

agent has a full global view of the system, or the system is too complex for an

agent to make practical use of such knowledge

Decentralisation

There

is no designated controlling agent (or the system is effectively reduced to a

monolithic system)

Self-organisation and self-steering

Multi-agent systems can manifest self-organisation as well

as self-steering and other control paradigms and related complex behaviors even

when the individual strategies of all their agents are simple.

Properties

The main feature which is achieved when developing

multi-agent systems, is flexibility, since a multi-agent system can be added

to, modified and reconstructed, without the need for detailed rewriting of the

application.

Study of multi-agent systems

IS-oriented agents Beliefs, desires and intentions (BDI) Cooperation and coordination Distributed Constraint Optimization Organization Communication Negotiation Distributed problem solving Multiagent Learning Mining agent Scientific communities Reliability and fault tolerance Robotics, multi-robot systems (MRS), robotic groups