Keeping planning problems as small as possible is a must in order to cope with complex tasks and environments. Earlier, we have described a method for cascading Description Logic (dl) representation and reasoning on the one hand, and Hierarchical Task Network (htn) action planning on the other. The planning domain description as well as the fundamental htn planning concepts are represented in dl and can therefore be subject to dl reasoning. From these representations, concise planning problems are generated for htn planners. We show by way of case study that this method yields significantly smaller planning problem descriptions than regular representations do in htn planning. The method is presented through a case study of a robot navigatio...
Despite the extensive development of first-principles planning in recent years, planning application...
This paper provides techniques for hierarchical task network (HTN) planning with durative actions. H...
Most practical work on AI planning systems during the last fifteen years has been based on hierarchi...
Keeping planning problems as small as possible is a must in order to cope with complex tasks and env...
We describe a method for cascading Description Logic (DL) representation and reasoning on the one ha...
Action planning has been used in the field of robotics for solving long-running tasks. In the robot ...
One big obstacle to understanding the nature of hierarchical task network (HTN) planning has been th...
Hierarchical Task Networks (HTN) planning uses a decomposition process guided by domain knowledge to...
We describe HTN-MAKER, an algorithm for learning hier-archical planning knowledge in the form of dec...
Hierarchical Task Network (HTN) planning is the problem of decomposing an initial task into a sequen...
To apply hierarchical task network (HTN) plan-ning to real-world planning problems, one needs to enc...
In planning based on hierarchical task networks (HTN), plans are generated by refining high-level ac...
Planning is a central activity in many areas including robotics, manufacturing, space mission sequen...
Hierarchical Task Network (HTN) planning is a formalism that can express constraints which cannot ea...
International audienceMany planning techniques have been developed to allow autonomous systems to ac...
Despite the extensive development of first-principles planning in recent years, planning application...
This paper provides techniques for hierarchical task network (HTN) planning with durative actions. H...
Most practical work on AI planning systems during the last fifteen years has been based on hierarchi...
Keeping planning problems as small as possible is a must in order to cope with complex tasks and env...
We describe a method for cascading Description Logic (DL) representation and reasoning on the one ha...
Action planning has been used in the field of robotics for solving long-running tasks. In the robot ...
One big obstacle to understanding the nature of hierarchical task network (HTN) planning has been th...
Hierarchical Task Networks (HTN) planning uses a decomposition process guided by domain knowledge to...
We describe HTN-MAKER, an algorithm for learning hier-archical planning knowledge in the form of dec...
Hierarchical Task Network (HTN) planning is the problem of decomposing an initial task into a sequen...
To apply hierarchical task network (HTN) plan-ning to real-world planning problems, one needs to enc...
In planning based on hierarchical task networks (HTN), plans are generated by refining high-level ac...
Planning is a central activity in many areas including robotics, manufacturing, space mission sequen...
Hierarchical Task Network (HTN) planning is a formalism that can express constraints which cannot ea...
International audienceMany planning techniques have been developed to allow autonomous systems to ac...
Despite the extensive development of first-principles planning in recent years, planning application...
This paper provides techniques for hierarchical task network (HTN) planning with durative actions. H...
Most practical work on AI planning systems during the last fifteen years has been based on hierarchi...