A rational agent is an artificial intelligence (AI) component. It applies AI to different real-world problems. As such, it chooses an action from a set of distinct options. It has models that allow it to deal with unexpected variables and always selects the best possible outcome from all the available options.

The term “rational agent,” however, is not only applied to a system. It can also refer to a person, a company, or an application, practically anything or anyone that makes rational decisions.

Other interesting terms…

Read More about a Rational Agent

The term “rational agent” traces its origin to economics. It is currently used in the field of AI to refer to applications meant to achieve specific goals.

In AI, rational agents are closely related to intelligent agents or autonomous programs that mimic human intelligence.

How Does a Rational Agent Work?

A rational agent is essentially a goal-based agent. It assesses its environment by considering what it is like. It then looks at each available action in its arsenal and determines how it will affect the environment and help it attain its goal. It tries out all the possible steps before choosing the best one, the one that will move it closest to its objective.

Here’s a simple diagram to help you understand.

What is a Rational Agent

A sensor could be a camera, an infrared device, a sonar, an ultrasound, a radar, or a lidar in the image above. It helps an AI robot determine an object’s or its surroundings’ size, identify a thing, and determine distances. An effector, meanwhile, is any device that affects a particular environment. It could be a robot’s legs, wheels, arms, fingers, wings, or fins. Effectors are also called “actuators.”

What Are the Real-World Applications of a Rational Agent?

A rational agent can be used for an autonomous vacuum cleaner. When it runs, it always looks at its surroundings to determine where it will go next. If something is preventing it from moving to the left (e.g., a sofa leg), it will consider moving to the right and do so if it can. It moves around a room, avoiding obstructions (i.e., furniture) while moving back and forth, sucking dirt when present.

Rational agents are also used in self-driving vehicles, energy-saving air-conditioning units, automated lights, and other devices that need environmental inputs to decide the best course of action to take.

What Makes a Rational Agent Effective?

A rational agent works if you can measure its performance. The higher its performance measure is, the more rational an agent is. Its performance measure is gauged using these criteria:

  • How well it achieves its goals
  • How well it assesses its environment
  • How many actions it can perform

A self-driving car, for example, is rational if it can bring you safely and comfortably where you need to go in the shortest amount of time. It needs to follow road signs and directions and avoid other vehicles, people, and other obstructions, including traffic.

Autonomous vehicles have sensors that include cameras, sonars, Global Positioning System (GPS) devices, speedometers, odometers, accelerometers, and keyboards. They also have actuators, including steering wheels, accelerators, brakes, signals, and horns.

What Are Examples of Rational Agents?

Rational agents make decisions based on certain criteria or principles to achieve their goals or maximize some notion of utility. Here are some examples across various domains.

  • Human beings: In many decision-making models, individuals are assumed to be rational agents, making choices based on their preferences and available information to achieve their goals.
  • Economic agents: In economics, rational agents are often used as a simplifying assumption. They include consumers who aim to maximize their utility given budget constraints and firms that aim to maximize profits given production costs and market conditions.
  • Robots and AI systems: Autonomous robots and AI systems can be designed as rational agents, making decisions based on programmed objectives, constraints, and sensory inputs.
  • Automated trading systems: In finance, algorithms used for automated trading are rational agents programmed to execute trades based on predefined criteria, such as market trends, price differentials, or statistical patterns.
  • Game-playing agents: Agents in game theory, such as players in strategic games like chess or poker, are often modeled as rational agents aiming to maximize their chances of winning based on the rules of the game and their understanding of opponents’ strategies.
  • Search algorithms: Algorithms used for searching through large solution spaces, such as those employed in optimization problems or pathfinding in AI, can be considered rational agents seeking the best possible solution given constraints and objectives.
  • Autonomous vehicles: Self-driving cars and other autonomous vehicles are designed as rational agents, making decisions about speed, direction, and actions based on sensor data and programmed rules to reach their destinations safely and efficiently.
  • Virtual assistants: AI-powered virtual assistants like Siri, Alexa, and Google Assistant can be seen as rational agents, interpreting user commands or queries and taking actions to provide relevant information or perform requested tasks.

So, what is a rational agent? Think of it as your brain, which tells parts of your body (e.g., your arms and legs) what to do when your sensors (e.g., eyes, ears, and nose) sense something in your surroundings you need to avoid so you will not get hurt.

Key Takeaways