Graph-based motor primitive generation framework
نویسندگان
چکیده
منابع مشابه
Resilience-Based Framework for Distributed Generation Planning in Distribution Networks
Events with low probability and high impact, which annually cause high damages, seriously threaten the health of the distribution networks. Hence, more attention to the issue of enhancing network resilience and continuity of power supply, feels more than ever, all over the world. In modern distribution networks, because of the increasing presence of distributed generation resources, an alternat...
متن کاملFramework for graph-based formalisms
Qualitative analysis and performance evaluation require the use of suitable formalisms to describe the systems under study. From an abstract point of view, most of the formalisms defined in the literature, can be seen as special kind of hierarchical graphs. In this work we present a framework for defining and manipulating graph-based formalisms. We build it on a data-definition language (or DDL...
متن کاملDistributed Graph-Based State Space Generation
LTSMIN provides a framework in which state space generation can be distributed easily over many cores on a single compute node, as well as over multiple compute nodes. The tool works on the basis of a vector representation of the states; the individual cores are assigned the task of computing all successors of states that are sent to them. In this paper we show how this framework can be applied...
متن کاملGraph-Based Generation of Referring Expressions
This article describes a new approach to the generation of referring expressions. We propose to formalize a scene (consisting of a set of objects with various properties and relations) as a labeled directed graph and describe content selection (which properties to include in a referring expression) as a subgraph construction problem. Cost functions are used to guide the search process and to gi...
متن کاملModel Selection Framework for Graph-based data
Graphs are powerful abstractions for capturing complex relationships in diverse application settings. An active area of research focuses on theoretical models that define the generative mechanism of a graph. Yet given the complexity and inherent noise in real datasets, it is still very challenging to identify the best model for a given observed graph. We discuss a framework for graph model sele...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Human-centric Computing and Information Sciences
سال: 2015
ISSN: 2192-1962
DOI: 10.1186/s13673-015-0051-0