The automated planning community has traditionally focused on the efficient synthesis of plans given a complete domain theory. In the past several years, this line of work met with significant successes, and the future course of the community seems to be set on efficient planning with even richer models. While this line of research has its applications, there are also many domains and scenarios where the first bottleneck is getting the domain model at any level of completeness. In these scenarios, the modeling burden automatically renders the planning technology unusable. To counter this, I will motivate model-lite planning technology aimed at reducing the domain-modeling burden (possibly at the expense of reduced functionality), and outlin...
There is increasing awareness in the planning community that depending on complete models impedes th...
The development of domain-independent planners within the AI Planning community is leading to “off...
Intelligent agents solving problems in the real world require domain models containing widespread kn...
The automated planning community has traditionally focused on the efficient synthesis of plans given...
This paper postulates a rigorous method for the construction of classical planning domain models. We...
This paper postulates a rigorous method for the construction of classical planning domain models. We...
AbstractThis paper postulates a rigorous method for the construction of classical planning domain mo...
The paper raises some issues relating to the engineering of domain models for automated planning. It...
We propose revisions to the research agenda in Automated Planning. The proposal is based on a review...
This paper concerns the area of automated acquisition of planning domain models from one or more exa...
In this commentary I argue that although pddl2.1 is a very useful standard for the planning competit...
Most current planners assume complete domain models and focus on generating correct plans. Unfortuna...
A great deal of emphasis in classical AI planning research has been placed on search-control issues ...
Planning via Model Checking is nowadays a well-known technique. Techniques based on model checking h...
Substantial improvements must be made in the usabil-ity of AI planning technologies in order for the...
There is increasing awareness in the planning community that depending on complete models impedes th...
The development of domain-independent planners within the AI Planning community is leading to “off...
Intelligent agents solving problems in the real world require domain models containing widespread kn...
The automated planning community has traditionally focused on the efficient synthesis of plans given...
This paper postulates a rigorous method for the construction of classical planning domain models. We...
This paper postulates a rigorous method for the construction of classical planning domain models. We...
AbstractThis paper postulates a rigorous method for the construction of classical planning domain mo...
The paper raises some issues relating to the engineering of domain models for automated planning. It...
We propose revisions to the research agenda in Automated Planning. The proposal is based on a review...
This paper concerns the area of automated acquisition of planning domain models from one or more exa...
In this commentary I argue that although pddl2.1 is a very useful standard for the planning competit...
Most current planners assume complete domain models and focus on generating correct plans. Unfortuna...
A great deal of emphasis in classical AI planning research has been placed on search-control issues ...
Planning via Model Checking is nowadays a well-known technique. Techniques based on model checking h...
Substantial improvements must be made in the usabil-ity of AI planning technologies in order for the...
There is increasing awareness in the planning community that depending on complete models impedes th...
The development of domain-independent planners within the AI Planning community is leading to “off...
Intelligent agents solving problems in the real world require domain models containing widespread kn...