In this paper we present the GraphHTN algorithm, a hybrid planning algorithm that does Hierarchical Task-Network (HTN) planning using a combination of HTNstyle problem reduction and Graphplan-style planninggraph generation. We also present experimental results comparing GraphHTN with ordinary HTN decomposition (as implemented in the UMCP planner) and ordinary Graphplan search (as implemented in the IPP planner). Our experimental results show that (1) the performance of HTN planning can be improved significantly by using planning graphs, and (2) that planning with planning graphs can be sped up by exploiting HTN control knowledge
One big obstacle to understanding the nature of hierarchical task network (HTN) planning has been th...
Planning is a central activity in many areas including robotics, manufacturing, space mission sequen...
appears in PLANSIG 2000 We describe a new planner that uses a genetic algorithm and domain-specific ...
Hierarchical Task Network (HTN) planning is the problem of decomposing an initial task into a sequen...
We describe HTN-MAKER, an algorithm for learning hier-archical planning knowledge in the form of dec...
International audienceMany planning techniques have been developed to allow autonomous systems to ac...
Hierarchical Task Network (HTN) planning (Sacerdoti 1974) is an approach to planning where problem-s...
In classical planning, the polynomial-time computability of propositional delete-free planning (plan...
Hierarchical Task Network (HTN) planning with Task Insertion (TIHTN planning) is a formalism that hy...
In applications of HTN planning, repeated problems have arisen from the lack of correspondence betw...
We describe HTN-Maker, an algorithm for learning hierarchical planning knowledge in the form of task...
Hierarchical Task Network (HTN) planning with task inser-tion (TIHTN planning) is a variant of HTN p...
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...
The Hierarchical Task Network (HTN) formalism is used to express a wide variety of planning problems...
One big obstacle to understanding the nature of hierarchical task network (HTN) planning has been th...
Planning is a central activity in many areas including robotics, manufacturing, space mission sequen...
appears in PLANSIG 2000 We describe a new planner that uses a genetic algorithm and domain-specific ...
Hierarchical Task Network (HTN) planning is the problem of decomposing an initial task into a sequen...
We describe HTN-MAKER, an algorithm for learning hier-archical planning knowledge in the form of dec...
International audienceMany planning techniques have been developed to allow autonomous systems to ac...
Hierarchical Task Network (HTN) planning (Sacerdoti 1974) is an approach to planning where problem-s...
In classical planning, the polynomial-time computability of propositional delete-free planning (plan...
Hierarchical Task Network (HTN) planning with Task Insertion (TIHTN planning) is a formalism that hy...
In applications of HTN planning, repeated problems have arisen from the lack of correspondence betw...
We describe HTN-Maker, an algorithm for learning hierarchical planning knowledge in the form of task...
Hierarchical Task Network (HTN) planning with task inser-tion (TIHTN planning) is a variant of HTN p...
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...
The Hierarchical Task Network (HTN) formalism is used to express a wide variety of planning problems...
One big obstacle to understanding the nature of hierarchical task network (HTN) planning has been th...
Planning is a central activity in many areas including robotics, manufacturing, space mission sequen...
appears in PLANSIG 2000 We describe a new planner that uses a genetic algorithm and domain-specific ...