Applications of Script Theory in AI

Script theory has been successfully applied in various AI domains to enhance understanding, prediction, and interaction capabilities:

Natural Language Processing (NLP):

Scripts help NLP systems understand and generate contextually relevant text.
Example: Chatbots use scripts to simulate conversations, understanding common sequences like greetings, information requests, and farewells.

Robotics:

Robots utilize scripts to perform complex tasks in a structured sequence.
Example: A household robot might follow a cleaning script that includes steps like “vacuuming the living room,” “dusting the shelves,” and “mopping the kitchen floor.”

Game AI:

Non-player characters (NPCs) use scripts to behave realistically and follow predictable patterns.
Example: In simulation games, NPCs might follow daily routines such as “waking up,” “going to work,” “eating lunch,” and “returning home.”

Event Prediction:

AI systems use scripts to predict future events based on historical data.
Example: Predictive maintenance systems in industrial settings use scripts to forecast equipment failures based on usage patterns and sensor data.

Script Theory in Artificial Intelligence

Script theory in Artificial Intelligence (AI) is a concept borrowed from cognitive psychology to help machines understand and predict human behavior by modeling sequences of events as predefined scripts. Originally proposed by cognitive scientist Roger Schank in the 1970s, script theory provides a framework for representing stereotypical sequences of actions in specific contexts, enabling AI systems to simulate human-like understanding and interaction.