2025 is projected as the year of the AI Agent.

Social media celebrates claims about automation making human tasks obsolete.

Understanding the distinction between simple and advanced AI agents.

Basic agent that follows predefined rules like a thermostat.

Operates on 'if condition, then action' principles.

Effective in predictable environments but can fail in dynamic scenarios.

An advanced reflex agent that uses an internal model of the world.

Tracks its actions and their effects on the environment.

Example: Robotic vacuum that remembers its cleaning path.

Decision-making is based on the agent's goals rather than fixed rules.

Predicts future outcomes to choose actions that help meet goals.

Example: Self-driving car navigates towards a destination.

Considers the desirability of different outcomes and ranks options.

Utilizes a happiness score to determine the best action.

Example: Autonomous drones optimizing delivery routes for efficiency.

Learns from experiences and adapts its actions based on feedback.

Employs a critic for evaluation and a problem generator for new actions.

Example: AI chess bot improving its strategy over time.

Multiple agents can operate in a shared environment collaboratively.

AI agents are adapting and evolving with generative AI.

Human involvement remains essential for effective operations.