Simple Reflex Agent: Reacts directly to current input without considering past or future outcomes. No internal memory.
Model-Based Reflex Agent: Enhances simple reflex agents by maintaining models of the environment.
Goal-Based Agent: Aims to achieve specific objectives by evaluating different actions.
Utility-Based Agent: Selects options based on expected utility (benefit or value).
Learning Agent: Modifies behavior based on experience and feedback.
Multi-Agent Systems: Involves multiple agents interacting to achieve collective goals.
Note : Each type of agent has its strengths and limitations, and they play different roles in AI systems and which one to deploy is based on the need of the situation.
Markdown for AI
A clean, structured version of this page for AI assistants and LLMs.
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Different types of AI agents can be listed as:
Note : Each type of agent has its strengths and limitations, and they play different roles in AI systems and which one to deploy is based on the need of the situation.