On Hierarchical Task Networks
نویسندگان
چکیده
In planning based on hierarchical task networks (HTN), plans are generated by refining high-level actions (‘compound tasks’) into lowerlevel actions, until primitive actions are obtained that can be sent to execution. While a primitive action is defined by its precondition and effects, a high-level action is defined by zero, one or several methods: sets of (high-level or primitive) actions decomposing it together with a constraint. We give a semantics of HTNs in terms of dynamic logic with program inclusion. We propose postulates guaranteeing soundness and completeness of action refinement. We also show that hybrid planning can be analysed in the same dynamic logic framework.
منابع مشابه
Hierarchical Task Network Planning as Satisfiability
The satissability paradigm has been hitherto applied to planning with only primitive actions. On the other hand, hierarchical task networks have been successfully used in many real world planning applications. Adapting the satissability paradigm to hierarchical task network planning, we show how the guidance from the task networks can be used to signiicantly reduce the sizes of the propositiona...
متن کاملFuzzy Hierarchical Location-Allocation Models for Congested Systems
There exist various service systems that have hierarchical structure. In hierarchical service networks, facilities at different levels provide different types of services. For example, in health care systems, general centers provide low-level services such as primary health care services, while the specialized hospitals provide high-level services. Because of demand congestion in service networ...
متن کاملMental Arithmetic Task Recognition Using Effective Connectivity and Hierarchical Feature Selection From EEG Signals
Introduction: Mental arithmetic analysis based on Electroencephalogram (EEG) signal for monitoring the state of the user’s brain functioning can be helpful for understanding some psychological disorders such as attention deficit hyperactivity disorder, autism spectrum disorder, or dyscalculia where the difficulty in learning or understanding the arithmetic exists. Most mental arithmetic recogni...
متن کاملLearning Probabilistic Hierarchical Task Networks to Capture User Preferences
While much work on learning in planning focused on learning domain physics (i.e., action models), and search control knowledge, little attention has been paid towards learning user preferences on desirable plans. Hierarchical task networks (HTN) are known to provide an effective way to encode user prescriptions about what constitute good plans. However, manual construction of these methods is c...
متن کاملLearning Probabilistic Hierarchical Task Networks from Plan Examples to Capture User Preference
Hierarchical task networks provide an efficient way to encode user prescriptions about what constitute good plans using component methods. However, manual construction of these methods is complex and time consuming. In this paper, we propose a novel approach to learning probabilistic hierarchical task networks that capture the user preference by examining user-produced plans given no prior info...
متن کاملHierarchical clustering analysis for visual - movement response functional MRI data processing
Cognitive experiments involving visual and movement tasks have been intensively studied using functional magnetic resonance imaging (fMRI). A common paradigm of such experiments is that subjects are required to complete different tasks such as visual task or movement task simultaneously. A key problem with these studies is how to identify various cerebral networks, even then all of them were ac...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2016