An intelligent agent needs knowledge about the real world for taking decisions and reasoning to act efficiently.
Knowledge-based agents are those agents who have the capability of maintaining an internal state of knowledge, reason about it, update it after observations and take actions.
These agents can represent the world with some formal representation and act intelligently.
A knowledge-based agent must able to do the following:
Knowledge-based agents are composed of two main parts:
The knowledge-based agent (KBA) take input from the environment by perceiving/monitoring it.
The input is taken and processed by the inference engine of the agent and which also communicate with KB to decide as per the knowledge stored in KB.
The learning element of KBA regularly updates the KB by learning new knowledge.
Knowledge-base is a central component of a knowledge-based agent, it is also known as KB.
A sentence is a proposition about the world.
Inference means deriving new sentences from old. Inference system allows us to add a new sentence to the knowledge base by applying logical rules to the KB to deduce new information.
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Inference engine is the component of the intelligent system in artificial intelligence, which applies logical rules to the knowledge base to infer new information from known facts.
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The first inference engine was part of the expert system.
Inference engine commonly proceeds in two modes, which are: