Visually based path-planning by Japanese monkeys

被引:35
|
作者
Mushiake, H [1 ]
Saito, N
Sakamoto, K
Sato, Y
Tanji, J
机构
[1] Tohoku Univ, Sch Med, Dept Physiol, Sendai, Miyagi 9808575, Japan
[2] Tohoku Univ, Sch Med, CREST, Sendai, Miyagi 9808575, Japan
[3] Tohoku Univ, Sch Med, Res Inst Elect Commun, Sendai, Miyagi 9808575, Japan
来源
COGNITIVE BRAIN RESEARCH | 2001年 / 11卷 / 01期
关键词
path-planning; prefered waypoint; maze; detour; monkey;
D O I
10.1016/S0926-6410(00)00067-7
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
To construct an animal model of strategy formation, we designed a maze path-finding task. First, we asked monkeys to capture a goal in the maze by moving a cursor on the screen. Cursor movement was linked to movements of each wrist. When the animals learned the association between cursor movement and wrist movement, we established a start and a goal in the maze, and asked them to find a path between them. We found that the animals took the shortest pathway, rather than approaching the goal randomly. We further found that the animals adopted a strategy of selecting a fixed intermediate point in the visually presented maze to select one of the shortest pathways, suggesting a visually based path planning. To examine their capacity to use that strategy flexibly, we transformed the rash; by blocking pathways in the maze, providing a problem to solve. The animals then developed a strategy of solving the problem by planning a novel shortest path from the start to the goal and rerouting the path to bypass the obstacle. (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:165 / 169
页数:5
相关论文
共 50 条
  • [1] Deceptive Path-Planning
    Masters, Peta
    Sardina, Sebastian
    [J]. PROCEEDINGS OF THE TWENTY-SIXTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2017, : 4368 - 4375
  • [2] The Grid-Based Path-Planning Competition
    Sturtevant, Nathan R.
    [J]. AI MAGAZINE, 2014, 35 (03) : 66 - 69
  • [3] Robot Path-planning based on Triangulation Tracing
    Gong, Faming
    Wang, Xin
    [J]. 2008 INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION WORKSHOP: IITA 2008 WORKSHOPS, PROCEEDINGS, 2008, : 713 - 716
  • [4] Extending the path-planning horizon
    Nabbe, Bart
    Hebert, Martial
    [J]. INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2007, 26 (10): : 997 - 1024
  • [5] Path-planning with virtual beams
    Hesse, Tobias
    Sattel, Thomas
    [J]. 2007 AMERICAN CONTROL CONFERENCE, VOLS 1-13, 2007, : 4767 - +
  • [6] A DDPG-Based USV Path-Planning Algorithm
    Zhao, Jian
    Wang, Pengrui
    Li, Baiyi
    Bai, Chunjiang
    [J]. APPLIED SCIENCES-BASEL, 2023, 13 (19):
  • [7] Hybrid Sensor Based Path-Planning for Autonomous Vehicle
    Samrat, Md Sadik
    Ali, Md Forhad
    Islam, Md Ashraful
    Hasan, Mehedi
    Hasan, Md Abid
    [J]. PROCEEDINGS OF INTERNATIONAL CONFERENCE ON ELECTRONICS, COMMUNICATIONS AND INFORMATION TECHNOLOGY 2021 (ICECIT 2021), 2021,
  • [8] Cost-Based Goal Recognition for Path-Planning
    Masters, Peta
    Sardina, Sebastian
    [J]. AAMAS'17: PROCEEDINGS OF THE 16TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS, 2017, : 750 - 758
  • [9] Sampling-based A* algorithm for robot path-planning
    Persson, Sven Mikael
    Sharf, Inna
    [J]. INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2014, 33 (13): : 1683 - 1708
  • [10] The multiple robots path-planning based on dynamic programming
    Yan, GZ
    Wang, Y
    Lin, LM
    [J]. PROCEEDINGS OF THE 4TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-4, 2002, : 1148 - 1152