This video introduces PDDL (Planning Domain Definition Language), explaining it's used to define AI planning problems. It breaks down PDDL into two main files:
The domain model (e.g., domain.pddl) describes the general rules and actions for a problem space (0:20, 1:42).
The problem instance (e.g., problem.pddl) defines a specific scenario, including initial and goal states (0:37, 5:06).
The video uses the Blocks World example to illustrate key concepts like:
Types: Categories for objects, similar to classes (2:05, 23:51).
Predicates: Describe facts or relationships between objects in a state (2:28, 24:01).
Action Schemas (Operators): Generic definitions of actions with parameters, preconditions (what must be true to perform the action), and effects (how the state changes after the action) (3:01, 10:36, 12:01, 16:51).
It also shows how to set up a VS Code environment with a PDDL extension to visualize and solve planning problems using a remote planner, outputting a plan (a sequence of actions) to reach the goal state (20:00, 27:47). Finally, it briefly introduces a Python API for unified planning as an alternative to directly writing PDDL files (31:54).
