(Also cross-referenced as ISR-TR-95-9) One big obstacle to understanding the nature of hierarchical task network (HTN) planning has been the lack of a clear theoretical framework. In particular, no one has yet presented a clear and concise HTN algorithm that is sound and complete. In this paper, we present a formal syntax and semantics for HTN planning. Based on this syntax and semantics, we are able to define an algorithm for HTN planning and prove it sound and complete. We also develop several definitions of expressivity for planning languages and prove that HTN Planning is strictly more expressive than STRIPS-style planning according to those definitions. (Also cross-referenced as UMIACS-TR-94-31
Abstract. It is widely believed, that the expressivity of STRIPS and STRIPS-like planning based on a...
AI Planning is a core technology in enabling advanced assistance for human users. When faced with c...
Keeping planning problems as small as possible is a must in order to cope with complex tasks and env...
One big obstacle to understanding the nature of hierarchical task network (HTN) planning has been th...
Despite the extensive development of first-principles planning in recent years, planning application...
(Also cross-referenced as ISR-TR-95-10) Most practical work on AI planning systems during the last ...
One big obstacle to understanding the nature of hierarchical task network (HTN) planning has been th...
Hierarchical Task Network (HTN) planning is the problem of decomposing an initial task into a sequen...
In applications of HTN planning, repeated problems have arisen from the lack of correspondence betw...
Hierarchical Task Networks (HTN) planning uses a decomposition process guided by domain knowledge to...
Hierarchical Task Network (HTN) planning is the problem of decomposing an initial task into a sequen...
Most practical work on AI planning systems during the last fifteen years has been based on hierarchi...
Planning is a central activity in many areas including robotics, manufacturing, space mission sequen...
We describe HTN-MAKER, an algorithm for learning hier-archical planning knowledge in the form of dec...
Hierarchical Task Network (HTN) planning with Task Insertion (TIHTN planning) is a formalism that hy...
Abstract. It is widely believed, that the expressivity of STRIPS and STRIPS-like planning based on a...
AI Planning is a core technology in enabling advanced assistance for human users. When faced with c...
Keeping planning problems as small as possible is a must in order to cope with complex tasks and env...
One big obstacle to understanding the nature of hierarchical task network (HTN) planning has been th...
Despite the extensive development of first-principles planning in recent years, planning application...
(Also cross-referenced as ISR-TR-95-10) Most practical work on AI planning systems during the last ...
One big obstacle to understanding the nature of hierarchical task network (HTN) planning has been th...
Hierarchical Task Network (HTN) planning is the problem of decomposing an initial task into a sequen...
In applications of HTN planning, repeated problems have arisen from the lack of correspondence betw...
Hierarchical Task Networks (HTN) planning uses a decomposition process guided by domain knowledge to...
Hierarchical Task Network (HTN) planning is the problem of decomposing an initial task into a sequen...
Most practical work on AI planning systems during the last fifteen years has been based on hierarchi...
Planning is a central activity in many areas including robotics, manufacturing, space mission sequen...
We describe HTN-MAKER, an algorithm for learning hier-archical planning knowledge in the form of dec...
Hierarchical Task Network (HTN) planning with Task Insertion (TIHTN planning) is a formalism that hy...
Abstract. It is widely believed, that the expressivity of STRIPS and STRIPS-like planning based on a...
AI Planning is a core technology in enabling advanced assistance for human users. When faced with c...
Keeping planning problems as small as possible is a must in order to cope with complex tasks and env...