Constraint Satisfaction
The problem of finding values for variables that satisfy a set of constraints. In AI, it is used in scheduling, planning, and configuration tasks.
Why It Matters
Constraint satisfaction is how AI solves real-world scheduling and allocation problems — from airline routing to factory scheduling to course timetabling.
Example
Finding a meeting time that satisfies constraints: all 5 attendees are available, a conference room is free, and it is during business hours — across 50 possible slots.
Think of it like...
Like solving a Sudoku puzzle — you need to find values that satisfy all the rules simultaneously, and the challenge grows with the number of constraints.
Related Terms
Planning
An AI agent's ability to break down complex goals into a sequence of steps and determine the best order of actions to accomplish a task. Planning involves reasoning about dependencies, priorities, and contingencies.
AI Agent
An AI system that can autonomously plan, reason, and take actions to accomplish goals. Unlike simple chatbots, agents can use tools, make decisions, execute multi-step workflows, and adapt their approach based on results.