Neural networks and structured knowledge: Knowledge representation and reasoning

被引：2
|
作者：
Kurfess, FJ [1 ]
机构：
[1] New Jersey Inst Technol, Dept Comp & Informat Sci, Newark, NJ 07102 USA
来源：
APPLIED INTELLIGENCE | 1999年 / 11卷 / 01期
关键词：
neural networks; knowledge representation; structured knowledge reasoning; connectionism; symbol processing; hybrid systems;
D O I：
10.1023/A:1008327412259
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This collection of articles is the first of two parts of a special issue on "Neural Networks and Structured Knowledge." The contributions to the first part shed some light on the issues of knowledge representation and reasoning with neural networks. Their scope ranges from formal models for mapping discrete structures like graphs or logical formulae onto different types of neural networks, to the construction of practical systems for various types of reasoning. In the second part to follow, the emphasis will be on the extraction of knowledge from neural networks, and on applications of neural networks and structured knowledge to practical tasks.
引用
收藏
页码：5 / 13
页数：9
相关论文
共 50 条
  • [1] Neural Networks and Structured Knowledge: Knowledge Representation and Reasoning
    Franz J. Kurfess
    [J]. Applied Intelligence, 1999, 11 : 5 - 13
  • [2] Commonsense knowledge representation and reasoning with fuzzy neural networks
    Kouzani, AZ
    He, F
    Sammut, K
    [J]. ANZIIS 96 - 1996 AUSTRALIAN NEW ZEALAND CONFERENCE ON INTELLIGENT INFORMATION SYSTEMS, PROCEEDINGS, 1996, : 237 - 240
  • [3] Integrating (rules, neural networks) and cases for knowledge representation and reasoning in expert systems
    Hatzilygeroudis, I
    Prentzas, J
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2004, 27 (01) : 63 - 75
  • [4] REASONING ABOUT STRUCTURED OBJECTS - KNOWLEDGE REPRESENTATION MEETS DATABASES
    BAADER, F
    BUCHHEIT, M
    JEUSFELD, MA
    NUTT, W
    [J]. KNOWLEDGE ENGINEERING REVIEW, 1995, 10 (01): : 73 - 76
  • [5] KNOWLEDGE REPRESENTATION AND REASONING
    LEVESQUE, HJ
    [J]. ANNUAL REVIEW OF COMPUTER SCIENCE, 1986, 1 : 255 - 287
  • [6] Cognitive Maps and Bayesian Networks for Knowledge Representation and Reasoning
    Sedki, Karima
    de Beaufort, Louis Bonneau
    [J]. 2012 IEEE 24TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2012), VOL 1, 2012, : 1035 - 1040
  • [7] On Representation Knowledge Distillation for Graph Neural Networks
    Joshi, Chaitanya K.
    Liu, Fayao
    Xun, Xu
    Lin, Jie
    Foo, Chuan Sheng
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2024, 35 (04) : 4656 - 4667
  • [8] Knowledge representation and possible worlds for neural networks
    Healy, Michael J.
    Caudell, Thomas P.
    [J]. 2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10, 2006, : 3047 - +
  • [9] Knowledge representation and analogical reasoning
    Klix, F
    Bachmann, T
    [J]. INTERNATIONAL JOURNAL OF PSYCHOLOGY, 1996, 31 (3-4) : 3184 - 3184
  • [10] Knowledge graph representation and reasoning
    Cambria, Erik
    Ji, Shaoxiong
    Pan, Shirui
    Yu, Philip S.
    [J]. Neurocomputing, 2021, 461 : 494 - 496
12345