Self-Learning AI Agents: A High-Level Overview

**Self-Learning AI Agents: A High-Level Overview**

Introduction Self-learning AI agents are systems that can recognize their environment, make decisions, take actions, and continuously improve their behavior based on feedback and experience. Unlike traditional rule-based software, these agents are not explicitly programmed for every possible scenario. Instead, they learn patterns, adapt to new situations, and refine their strategies over time. This ability to learn autonomously makes self-learning agents especially useful in complex and dynamic environments such as recommendation systems, robotics, autonomous navigation, finance, and intelligent assistants. At their core, self-learning AI agents combine ideas from machine learning, reinforcement learning, decision theory, and large language models...

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