What is an Intelligent Agent?
An intelligent agent (IA) in the Artificial Intelligence (AI) is a programme that can make decisions or perform a service based on the environment, input and experience. Intelligent agents are used to autonomously collect information on a regular programmable schedule or on demand by the user in real time.
Such agents are also called bots. This technique, where information is delivered by an agent, is called push technology.
There are different types of intelligent agents, such as Reflection agents, model-based agents, goal-based agents, utility-based agents and learning agents. These types of intelligent agents are practically defined by their range of capabilities and functions. Examples of these agents are Alexa and Siri. These use sensors to communicate with the user.
The Intelligent Agent Architecture has a combination of agent functions, architecture and agent programmes. This architecture is a machinery on the basis of which the agent performs its actions. Essentially, it is a device in which there are embedded actuators and sensors. For example, autonomous vehicles exist with motion and GPS sensors. There are also actuators based on inputs that support actual driving.
Where is IA used in artificial intelligence?
Widespread techniques in which AI is successfully used include industrial robots and automated production facilities, quality assurance, with Automatic image recognition, and with Speech recognition and Speech extractionand also in weather or stock market forecasts and in knowledge-based expert systems.
Types of Intelligent Agents
Types of IA include:
- modal adaptive,
- and social agents.
Intelligent agents are characterised by knowledge, the ability to learn and the ability to make inferences. These agents also have the ability to change behaviour.
An intelligent software agent can act flexibly. It is reactive, proactive and social. Such an IA can act autonomously in its environment. It performs its tasks on behalf of a user or other agents.
An Intelligent Agent exhibits the ability to use task-oriented problem solving through an autonomous, reactive and goal-oriented application of appropriate Artificial Intelligence methods. It uses a corresponding knowledge representation in its environment with the associated actions and goals. The IA uses logical reasoning and heuristic solution seeking when planning. He uses machine learning and can handle uncertain knowledge. Intelligent interaction is possible with it, with visualisation and natural language dialogue.
There are simple reactive agents, status-based reflex agents, practical reasoning (planning) agents and learning agents. In social agents, there are robust and distributed collaborations with various other agents for individual or shared tasks and goals. And in a multi-agent system, interacting agents pursue distributed problem solving. There is hierarchical task distribution and emergent solution behaviour (with swarm intelligence). There is also coordination in the system, with communication between the agents and with different cooperation models.