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Types of Agents in Artificial Intelligence

In this tutorial, you will learn about the types of agents and also learn on which basis such classification of the agents has been created? By Monika Sharma Last updated : April 12, 2023

Agents can be grouped into four classes based on their degree of perceived intelligence and capability. These are:

1. Simple reflex agents

• This agent works only on the basis of current perception and it does not bother about the history or previous state in which the system was.
• This type of agent is based upon the condition-action rule. If the condition is true, then the action is taken, else not.
• PROBLEMS FACED:
  1. Very limited intelligence.
  2. No knowledge about the non-perceptual parts of the state.
  3. Operating in a partially observable environment, infinite loops are unavoidable.

2. Model based reflex agents

• It works by finding a rule whose condition matches the current situation.
• It can handle partially observable environments.
• Updating the state requires information about how the world evolves independently from the agent and how the agent actions affect the world.

3. Goal based reflex agents

• The goal based agent focuses only on reaching the goal set and hence the decision took by the agent is based on how far it is currently from their goal or desired state.
• Their every action is intended to minimize their distance from the goal.
• This agent is more flexible, and the agent develops its decision making skill by choosing the right from the various options available.

4. Utility based agents

• These agents are more concerned about the preference(utility) for each state. When there are multiple options available, the utility based agent takes the decision on the basis that how much satisfaction the agent gets from it.
• This approach was like somewhat adding emotions to the agent, because, after taking any decision, the agent ensures that "how happy I Am after taking this decision?".
• This agent was developed because sometimes achieving the desired goal is not enough. We may look for quicker, safer and cheaper alternate to reach the destination.

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