5 Types of AI Agents Autonomous Functions & Real-World Applications
AI Summary
In this insightful video, Martin Keen from IBM Technology discusses the five main types of AI agents that are transforming automation and decision-making in various industries. He breaks down the distinctions between these agents:
- Simple Reflex Agents: These are basic agents that follow predefined rules to make decisions, like a thermostat which reacts to temperature changes.
- Model-Based Reflex Agents: They improve upon simple reflex agents by incorporating an internal model of the world, enabling them to update their actions based on previous states, such as a robotic vacuum that remembers its cleaning path.
- Goal-Based Agents: These agents focus on achieving specific goals and consider possible future states when making decisions, exemplified by self-driving cars that navigate towards destinations.
- Utility-Based Agents: They evaluate different outcomes based on desirability, choosing options that maximize overall ‘happiness’ or efficiency, such as drones optimizing package delivery routes.
- Learning Agents: The most advanced type, which learns from experience and feedback to improve performance over time, like an AI chess bot that refines its strategies through trials.
The video emphasizes that while AI agents are becoming increasingly capable, effective collaboration with human oversight remains crucial for optimal results.