Towards an Understanding of Hierarchical Architectures

被引：4
|
作者：
Goerick, Christian [1 ]
机构：
[1] Honda Res Inst Europe GmbH, D-63073 Offenbach, Germany
来源：
IEEE TRANSACTIONS ON AUTONOMOUS MENTAL DEVELOPMENT | 2011年 / 3卷 / 01期
关键词：
Behavior space; cognitive architecture; hierarchical architecture; sensor space; system design; SYSTEMS;
D O I：
10.1109/TAMD.2010.2089982
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Cognitive systems research aims to understand how cognitive abilities can be created in artificial systems. One key issue is the architecture of the system. It organizes the interplay between the different system elements and thus, determines the principle limits for the performance of the system. In this contribution, we focus on important properties of hierarchical cognitive systems. Therefore, we first present a framework for modeling hierarchical systems. Based on this framework, we formulate and discuss some crucial issues that should be treated explicitly in the design of a system. On this basis, we analyze and compare several well-established cognitive architectures with respect to their internal structure.
引用
收藏
页码：54 / 63
页数：10
相关论文
共 50 条
  • [1] Towards Hierarchical Information Architectures in Automotive Systems
    Jobst, Martin Erich
    Prehofer, Christian
    [J]. 2016 3RD INTERNATIONAL WORKSHOP ON EMERGING IDEAS AND TRENDS IN ENGINEERING OF CYBER-PHYSICAL SYSTEMS (EITEC), 2016, : 41 - 46
  • [2] Towards an Understanding of Technical Debt in Reference Architectures
    Damaceno, Katia
    Nakagawa, Elisa Yumi
    Braga, Rosana
    [J]. 36TH BRAZILIAN SYMPOSIUM ON SOFTWARE ENGINEERING, SBES 2022, 2022, : 257 - 262
  • [3] Hierarchical algorithms on hierarchical architectures
    Keyes, D. E.
    Ltaief, H.
    Turkiyyah, G.
    [J]. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2020, 378 (2166):
  • [4] Towards understanding the hierarchical nitrogen signalling network in plants
    Zhang, Zhihua
    Hu, Bin
    Chu, Chengcai
    [J]. CURRENT OPINION IN PLANT BIOLOGY, 2020, 55 : 60 - 65
  • [5] Towards Understanding Hierarchical Learning: Benefits of Neural Representations
    Chen, Minshuo
    Bai, Yu
    Lee, Jason D.
    Zhao, Tuo
    Wang, Huan
    Xiong, Caiming
    Socher, Richard
    [J]. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 33, NEURIPS 2020, 2020, 33
  • [6] Towards understanding hierarchical clustering: A data distribution perspective
    Wu, Junjie
    Xiong, Hui
    Chen, Jian
    [J]. NEUROCOMPUTING, 2009, 72 (10-12) : 2319 - 2330
  • [7] Choice Architectures in the Digital Economy: Towards a New Understanding of Digital Vulnerability
    Helberger, N.
    Sax, M.
    Strycharz, J.
    Micklitz, H-W
    [J]. JOURNAL OF CONSUMER POLICY, 2022, 45 (02) : 175 - 200
  • [8] Choice Architectures in the Digital Economy: Towards a New Understanding of Digital Vulnerability
    N. Helberger
    M. Sax
    J. Strycharz
    H.-W. Micklitz
    [J]. Journal of Consumer Policy, 2022, 45 : 175 - 200
  • [9] LEARNERS' UNDERSTANDING OF THE DEFINITIONS AND HIERARCHICAL CLASSIFICATION OF QUADRILATERALS: TOWARDS A THEORETICAL FRAMING
    Fujita, Taro
    Jones, Keith
    [J]. RESEARCH IN MATHEMATICS EDUCATION, 2007, 9 (01) : 3 - 20
  • [10] ρ:: Hierarchical modeling of parallel architectures
    Weper, R
    Zehendner, E
    Erhard, W
    [J]. PROCEEDINGS OF THE SEVENTH EUROMICRO WORKSHOP ON PARALLEL AND DISTRIBUTED PROCESSING, PDP'99, 1999, : 233 - 240
12345