Summary
In this chapter, we discussed several aspects and key components of intelligent agents. We started with the understanding and importance of various knowledge representation mechanisms such as semantic networks, frames, and logic-based representations. We also learned about various reasoning techniques such as deductive, inductive, and abductive reasoning to understand how intelligent agents may use these techniques for decision-making to accomplish tasks. We briefly looked at some of the learning mechanisms that intelligent agents may use to adapt themselves to various use cases and explored agent decision-making via utility functions and various planning algorithms. Finally, we wrapped up this chapter with an introduction to intelligent agents with generative AI using an LLM and discussed a simple intelligent agent that is capable of gathering information from user queries for our travel booking agent example.
In the next chapter, we will dive deeper into the advanced intelligent...
