Discovery as Autonomous Learning from the Environment
Abstract
Discovery involves collaboration among many intelligent activities. However, little is known about how and in what form such collaboration occurs. In this article, a framework is proposed for autonomous systems that learn and discover from their environment. Within this framework, many intelligent activities such as perception, action, exploration, experimentation, learning, problem solving, and new term construction can be integrated in a coherent way. The framework is presented in detail through an implemented system called LIVE, and is evaluated through the performance of LIVE on several discovery tasks. The conclusion is that autonomous learning from the environment is a feasible approach for integrating the activities involved in a discovery process.
Cite
Text
Shen. "Discovery as Autonomous Learning from the Environment." Machine Learning, 1993. doi:10.1007/BF00993064Markdown
[Shen. "Discovery as Autonomous Learning from the Environment." Machine Learning, 1993.](https://mlanthology.org/mlj/1993/shen1993mlj-discovery/) doi:10.1007/BF00993064BibTeX
@article{shen1993mlj-discovery,
title = {{Discovery as Autonomous Learning from the Environment}},
author = {Shen, Wei-Min},
journal = {Machine Learning},
year = {1993},
pages = {143-165},
doi = {10.1007/BF00993064},
volume = {12},
url = {https://mlanthology.org/mlj/1993/shen1993mlj-discovery/}
}