首页 | 本学科首页   官方微博 | 高级检索  
     


Human breeders for evolving robots
Authors:Orazio Miglino  Onofrio Gigliotta  Michela Ponticorvo  Henrik H Lund
Affiliation:(1) Department of Relational Sciences, University of Naples “Federico II”, Naples, 80133, Italy;(2) Institute of Cognitive Sciences and Technologies, National Research Council, Rome, 00185, Italy;(3) Department of Psychology, University of Palermo, Palermo, 90100, Italy;(4) The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, DK-5230, Denmark
Abstract:In this article we describe a new approach in evolutionary robotics according to which human breeders are involved in the evolutionary process. While traditionally robots are selected to reproduce automatically according to a fitness formula, which is a quantitative and strictly defined measure, human breeders can operate selection based on qualitative criteria, and rewarding behaviors that can slip between the meshes woven by the fitness formula. In authors’ opinion this may bring advantages to the evolutionary robotics methodology, allowing the production of robots that display more, and more multiform, behaviors. In order to illustrate this approach, the software Breedbot was developed in which human breeders can intervene in evolving robots, complementing the automatic evaluation. After describing the software, some results on sample evolutionary processes are reported showing that the joint use of human and artificial selection on an exploration task generates robots with a higher performance and in a shorter time compared with the exclusive action of each breeding method. Future work will explore this hypothesis further. This work was presented in part at the First European Workshop on Artificial Life and Robotics, Vienna, Austria, July 12–13, 2007
Keywords:User-guided evolutionary robotics  Human-robot interaction  Fitness function
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号