Integration of constraint logic programming and artificial neural networks for driving robots

被引：0
|
作者：
Ishikawa, K [1 ]
Fujinami, T [1 ]
Sakurai, A [1 ]
机构：
[1] Japan Adv Inst Sci & Technol, Grad Sch Knowledge Sci, Tatsunokuchi, Ishikawa 9231292, Japan
来源：
IROS 2001: PROCEEDINGS OF THE 2001 IEEE/RJS INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-4: EXPANDING THE SOCIETAL ROLE OF ROBOTICS IN THE NEXT MILLENNIUM | 2001年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We propose a robot architecture to integrate symbolic and non-symbolic information processings. Artificial neural networks (ANN) are quick, flexible and robust. Symbolic processing is on the other hand comprehensible, effective, controllable, and consistent. To integrate symbolic and non-symbolic methods, we consider the relation between a robot and its environment as constraints. To describe and solve such constraints we turn to Constraint Logic Programming (CLP). To construct a robot that works in the complex environment, CLP and ANN are integrated into a unified framework such that CLP evaluates the behavior candidates proposed by ANN according to the constraints and ANN learns adequate behavior according to evaluations by CLP. We implemented the decision process in our robot that drove through a test course as we expected.
引用
收藏
页码：1011 / 1016
页数：6
相关论文
共 50 条
  • [11] Constraint logic programming
    Wallace, M
    [J]. COMPUTATIONAL LOGIC: LOGIC PROGRAMMING AND BEYOND, PT I: ESSAYS IN HONOUR OF ROBERT A KOWALSKI, 2002, 2407 : 512 - 532
  • [12] Fuzzy Logic Programming for Tuning Neural Networks
    Moreno, Gines
    Perez, Jesus
    Riaza, Jose A.
    [J]. RULES AND REASONING (RULEML+RR 2019), 2019, 11784 : 190 - 197
  • [13] Implementation of Trajectory Planning for Automated Driving Systems using Constraint Logic Programming
    Wriedt, Christian
    Beierle, Christoph
    [J]. PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE (ICAART), VOL 2, 2019, : 411 - 418
  • [14] Artificial Neural Networks manipulation server:: Research on the integration of databases and Artificial Neural Networks
    Santos, A
    Arcay, B
    Dorado, J
    Rodríguez, AB
    Pazos, A
    [J]. NEURAL COMPUTING & APPLICATIONS, 2002, 11 (01): : 3 - 16
  • [15] Artificial Neural Networks Manipulation Server: Research on the Integration of Databases and Artificial Neural Networks
    A. Santos
    B. Arcay
    J. Dorado
    A.B. Rodríguez
    A. Pazos
    [J]. Neural Computing & Applications, 2002, 11 : 3 - 16
  • [16] Artificial Neural Networks and Logic Circuit Synthesis
    Gurov S.I.
    Zolotarev D.V.
    Samburskii A.I.
    [J]. Computational Mathematics and Modeling, 2021, 32 (4) : 490 - 499
  • [17] Functional and constraint logic programming
    Rodríguez-Artalejo, M
    [J]. CONSTRAINTS IN COMPUTATIONAL LOGICS: THEORY AND APPLICATIONS, 2001, 2002 : 202 - 270
  • [18] NEGATION AND CONSTRAINT LOGIC PROGRAMMING
    STUCKEY, PJ
    [J]. INFORMATION AND COMPUTATION, 1995, 118 (01) : 12 - 33
  • [19] CONSTRAINT LOGIC PROGRAMMING - A SURVEY
    JAFFAR, J
    MAHER, MJ
    [J]. JOURNAL OF LOGIC PROGRAMMING, 1994, 20 : 503 - 581
  • [20] CONSTRAINT SATISFACTION USING CONSTRAINT LOGIC PROGRAMMING
    VANHENTENRYCK, P
    SIMONIS, H
    DINCBAS, M
    [J]. ARTIFICIAL INTELLIGENCE, 1992, 58 (1-3) : 113 - 159
12345