Real-world examples of state machines in action

Are you curious about how state machines work in real-world applications? Look no further! In this article, we'll explore some exciting examples of state machines in action.

What is a state machine?

Before diving into the examples, let's quickly review what a state machine is. A state machine is a mathematical model used to describe the behavior of a system. It consists of a set of states, transitions between those states, and actions that occur when a transition is made. State machines are used in a variety of applications, from software development to robotics.

Example 1: Traffic light control

One of the most common examples of a state machine is traffic light control. Traffic lights have three states: green, yellow, and red. The transitions between these states are triggered by timers or sensors. For example, when a timer runs out, the green light transitions to yellow, and then to red. When a sensor detects a car waiting at a red light, the red light transitions to green.

But traffic light control is not just a simple state machine. There are also complex rules that govern the behavior of the system. For example, if a pedestrian presses a button, the system must transition to a state that allows the pedestrian to cross the street safely. This requires additional states and transitions, as well as actions such as flashing lights and audible signals.

Example 2: Vending machines

Another example of a state machine is a vending machine. Vending machines have a set of states that describe the current state of the machine, such as "idle", "dispensing", and "out of stock". Transitions between these states are triggered by user input, such as pressing a button or inserting money.

But vending machines also have complex rules that govern their behavior. For example, if a user selects an item that is out of stock, the machine must transition to a state that informs the user of the problem and returns their money. This requires additional states and transitions, as well as actions such as displaying an error message and returning the user's money.

Example 3: Elevator control

Elevator control is another example of a state machine. Elevators have a set of states that describe the current state of the elevator, such as "idle", "moving up", and "moving down". Transitions between these states are triggered by user input, such as pressing a button or opening a door.

But elevator control is also complex, with rules that govern the behavior of the system. For example, if a user presses a button for a floor that is already occupied, the system must transition to a state that informs the user of the problem and waits for the elevator to become available. This requires additional states and transitions, as well as actions such as displaying an error message and waiting for the elevator to become available.

Example 4: Game AI

State machines are also used in game development to control the behavior of non-player characters (NPCs). NPCs have a set of states that describe their current behavior, such as "idle", "patrolling", and "attacking". Transitions between these states are triggered by events in the game, such as the player entering a certain area or the NPC taking damage.

But game AI is also complex, with rules that govern the behavior of the NPCs. For example, if an NPC is attacked by the player, the system must transition to a state that causes the NPC to defend itself or flee. This requires additional states and transitions, as well as actions such as attacking the player or running away.

Conclusion

State machines are a powerful tool for modeling complex systems. They are used in a variety of applications, from traffic light control to game development. By understanding how state machines work and how they are used in real-world applications, you can gain a deeper appreciation for the power of this mathematical model. So the next time you encounter a complex system, ask yourself: could this be modeled using a state machine?

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Written by AI researcher, Haskell Ruska, PhD (haskellr@mit.edu). Scientific Journal of AI 2023, Peer Reviewed