PDDL
Planning Domain Definition Language, a language for standardized modeling of planning problems. It separates a problem into a domain file and a problem file and supports subsets ranging from STRIPS to PDDL+.
Timeline (last 90 days)
Kairos is a framework that selects heterogeneous planning engines according to the semantics of each task, covering a broad range from STRIPS to PDDL+.
Single dedicated planners differ significantly in PDDL coverage, latency, and the meaning of failure, and the meaning of failure is not unified (unsolvable, timeout, and out-of-memory are hard to distinguish).
PDDL is a standardized modeling language promoted and shaped by the International Planning Competition (IPC), which splits a planning problem into two files: domain and problem.
The most representative symbolic planning method is automated planning technology, with typical implementations including formal languages such as STRIPS and PDDL, as well as search-based planners.
In the AI field, goal representations span multiple technical paradigms: reinforcement learning uses reward functions, classical planning uses first-order logic languages such as PDDL, inverse reinforcement learning infers goals from behavior, and large language models use natural-language instructions.
In formal planning systems such as PDDL, a task is defined as a transition from an initial state to a goal state, rather than a fixed sequence of actions
All Facts (6)
Kairos is a framework that selects heterogeneous planning engines according to the semantics of each task, covering a broad range from STRIPS to PDDL+.
50%UnverifiedSingle dedicated planners differ significantly in PDDL coverage, latency, and the meaning of failure, and the meaning of failure is not unified (unsolvable, timeout, and out-of-memory are hard to distinguish).
50%UnverifiedPDDL is a standardized modeling language promoted and shaped by the International Planning Competition (IPC), which splits a planning problem into two files: domain and problem.
50%UnverifiedThe most representative symbolic planning method is automated planning technology, with typical implementations including formal languages such as STRIPS and PDDL, as well as search-based planners.
50%UnverifiedIn the AI field, goal representations span multiple technical paradigms: reinforcement learning uses reward functions, classical planning uses first-order logic languages such as PDDL, inverse reinforcement learning infers goals from behavior, and large language models use natural-language instructions.
50%UnverifiedIn formal planning systems such as PDDL, a task is defined as a transition from an initial state to a goal state, rather than a fixed sequence of actions
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