While in most planning approaches goals and plans are different objects, it is often useful to specify goals that combine declarative conditions with procedural plans. In this paper, we propose a novel language for expressing temporally extended goals for planning in nondeterministic domains. The key feature of this language is that it allows for an arbitrary combination of declarative goals ex...

Planning has been at the forefront of research in the areas of Artificial Intelligence and cognitive science. High-level action description languages (e.g., language A) have been used to specify, verify and diagnose plans. Timed Planning is planning under real-time constraints. To specify timed planning problems, an extension of the action description language A with real-time stopwatches, call...

This paper presents an approach to artificial intelligence planning based on linear temporal logic (LTL). A simple and easy-to-use planning language is described, PDDL-K (Planning Domain Description Language with control Knowledge), which allows one to specify a planning problem together with heuristic information that can be of help for both pruning the search space and finding better quality ...

The declarative language Picat has recently entered the scene of constraint logic programming, in particular thanks to the efficiency of its planning library that exploits a clever implementation of tabling, inherithed in part from B-Prolog. Planning benchmarks, used in competitions, are defined in the language PDDL and this implied that Picat users were forced to reimplement those models withi...

Planning is a very important AI problem and it is also a very time consuming AI problem To get an idea of how complex dif ferent planning problems are it is useful to describe the computational complexity of di erent general planning problems This complexity has been described for problems in which planning is based on the complete or partial information about the current state of the system In...

The planning domain language PDDL2.1, used in the 3rd International Planning Competition, has sparked off some controversy in the planning community as researchers consider its expressive power and the ease with which interesting domain models can be constructed in the language. In this paper we show that the expressive power of PDDL2.1 is much greater than is commonly believed. We demonstrate ...