Planning Domain Definition Language (PDDL)
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A Planning Domain Definition Language (PDDL) is an domain-specific language for automated planning and scheduling.
- Context:
- It can (typically) define planning problems in terms of states, actions, and goals.
- It can (often) be extended through new versions to handle more complex features such as time, resources, and non-deterministic outcomes.
- It can range from basic versions (handling only classical planning) to more advanced versions (incorporating temporal or probabilistic planning).
- It can be utilized in heuristic search planning algorithms for solving optimization problems.
- It can be integrated with various AI Planning Systems, such as Fast Downward and Metric-FF, to execute planning tasks.
- It can serve as a common benchmark language in the International Planning Competition for evaluating automated planners.
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- Example(s):
- PDDL 1.2 that introduced handling of simple conditional effects and served as a foundation for classical planning problems.
- PDDL 2.1 that introduced support for temporal planning and numeric fluents, allowing the representation of actions with durations and the use of numeric variables.
- PDDL 3.0 that incorporated soft constraints and preferences, expanding its utility for real-world applications where some goals may be more desirable than others.
- PDDL+ that further extended the language to support continuous change and hybrid systems, enabling the representation of complex, real-time dynamic systems.
- ...
- Counter-Example(s):
- Finite-State Machines (FSM), which are not suited for solving complex planning problems but rather focus on pre-defined state transitions.
- Business Process Model and Notation (BPMN), which is used for business process modeling and lacks the flexibility needed for AI-based automated planning.
- See: International Planning Competition, Drew McDermott, Planning Task.
References
2024
- (Wikipedia, 2024) ⇒ https://en.wikipedia.org/wiki/Planning_Domain_Definition_Language Retrieved:2024-9-24.
- The Planning Domain Definition Language (PDDL) is an attempt to standardize Artificial Intelligence (AI) planning languages.[1] It was first developed by Drew McDermott and his colleagues in 1998 mainly to make the 1998/2000 International Planning Competition (IPC) possible, and then evolved with each competition. The standardization provided by PDDL has the benefit of making research more reusable and easily comparable, though at the cost of some expressive power, compared to domain-specific systems.[2]