1.1.2 Historical Evolution of AI Agents

The concept of an agent has a long history, dating back to philosophers like Aristotle and Hume. The term was later adopted in computer science to describe programs that could act on behalf of users. As AI research progressed, the term "agent" became associated with artificial entities that could exhibit intelligent behavior.

Early AI agents were based on symbolic AI, using logical rules and representations to reason and make decisions. However, these agents were limited in their ability to adapt to new situations.

Later, AI agents incorporated machine learning techniques, allowing them to learn from data and improve their performance over time.

The recent emergence of Large Language Models (LLMs) has led to a new generation of AI agents with advanced capabilities. These agents can understand and process language, reason about complex problems, and even use tools to complete tasks.