5 Types of AI Agents Autonomous Functions & Real-World Applications
AI Summary
Overview of AI Agents in 2025
- AI Agents Classification: Agents are classified by intelligence levels, decision-making processes, and their interaction with the environment.
Types of AI Agents
- Simple Reflex Agent
- Makes decisions based on predefined rules.
- Example: Thermostat (turns on heat below a set threshold).
- Limited to predictable environments.
- Model-Based Reflex Agent
- Uses internal world models, updates state based on observations.
- Example: Robotic vacuum cleaner (remembers past movements and obstacles).
- Goal-Based Agent
- Decision-making based on achieving goals.
- Example: Self-driving cars (predict actions based on current state to reach destinations).
- Utility-Based Agent
- Ranks outcomes based on desirability (utility).
- Example: Autonomous drone delivery (chooses routes maximizing efficiency and safety).
- Learning Agent
- Learns from experience and feedback to improve performance.
- Components: Critic (observes outcomes), Learning Element (updates knowledge), Problem Generator (suggests new actions).
- Example: AI chess bot (adjusts strategies based on past games).
Multi-Agent Systems
- Collaboration: Multiple agents work cooperatively in a shared environment to achieve goals.
- Human in the Loop: Human oversight is often necessary, highlighting that AI is not yet fully autonomous.