The last decade has witnessed a dramatic progress in the variety and performance of techniques and tools for classical planning. Much of this can be ascribed to the existence of a de-facto standard modeling language for classical planning, PDDL. PDDL has fostered information sharing and data exchange in the planning community, and has made international classical planning competitions possible. At the same time, in the last few years, non-classical planning has gained considerable attention, due to its capability to capture relevant features of real-life domains which the classical framework fails to express. However, no significant effort has been made to achieve a standard means for expressing non-classical problems, making it difficul...
Comunicació presentada a la Twenty-Sixth International Joint Conference on Artificial Intelligence (...
AbstractRarely planning domains are fully observable. For this reason, the ability to deal with part...
There have been several proposals for expressing planning problems with different forms of uncertain...
The last decade has witnessed a dramatic progress in the variety and performance of techniques and t...
This paper proposes a framework for planning under uncertainty given a partially known initial state...
International audienceWe study different languages for representing nondeterministic actions in plan...
PDDL2.1 was designed to push the envelope of what planning algorithms can do, and it has succeeded. ...
Planning with partial observability can be formulated as a non-deterministic search problem in belie...
Planning is the branch of Artificial Intelligence (AI) that seeks to automate reasoning about plans,...
This paper presents an optimal planner for the international probabilistic planning competition at I...
PDDL is a language for specifying deterministic planning domains and problems. We describe the basic...
Automated planning is the field of Artificial Intelligence (AI) that focuses on identifying sequence...
Hybrid PDDL+ models are amongst the most advanced models of systems and the resulting problems are n...
Rarely planning domains are fully observable. For this reason, the ability to deal with partial obse...
This paper describes POND, a planner developed to solve problems characterized by partial observabil...
Comunicació presentada a la Twenty-Sixth International Joint Conference on Artificial Intelligence (...
AbstractRarely planning domains are fully observable. For this reason, the ability to deal with part...
There have been several proposals for expressing planning problems with different forms of uncertain...
The last decade has witnessed a dramatic progress in the variety and performance of techniques and t...
This paper proposes a framework for planning under uncertainty given a partially known initial state...
International audienceWe study different languages for representing nondeterministic actions in plan...
PDDL2.1 was designed to push the envelope of what planning algorithms can do, and it has succeeded. ...
Planning with partial observability can be formulated as a non-deterministic search problem in belie...
Planning is the branch of Artificial Intelligence (AI) that seeks to automate reasoning about plans,...
This paper presents an optimal planner for the international probabilistic planning competition at I...
PDDL is a language for specifying deterministic planning domains and problems. We describe the basic...
Automated planning is the field of Artificial Intelligence (AI) that focuses on identifying sequence...
Hybrid PDDL+ models are amongst the most advanced models of systems and the resulting problems are n...
Rarely planning domains are fully observable. For this reason, the ability to deal with partial obse...
This paper describes POND, a planner developed to solve problems characterized by partial observabil...
Comunicació presentada a la Twenty-Sixth International Joint Conference on Artificial Intelligence (...
AbstractRarely planning domains are fully observable. For this reason, the ability to deal with part...
There have been several proposals for expressing planning problems with different forms of uncertain...