Journal article
Learning how to plan
Robotics and autonomous systems, Vol.8(1), pp.93-111
1991
DOI: 10.1016/0921-8890(91)90016-E
Abstract
The construction of intelligent autonomous systems is a core goal of artificial intelligence. Research in machine learning yields some insight in how autonomous systems could learn to plan more effectively. This paper describes an application of
explanation-based learning, or
EBL, to a robot manufacturing domain. The ARMS system (for
Acquiring Robotic Manufacturing Schemata) learns how to assemble new mechanisms by observing and analyzing another agent's solution to sample assembly problems. While the ARMS system's major contribution is in the area of machine learning, the lessons learned from this work are readily applicable to autonomous agent research.
Details
- Title: Subtitle
- Learning how to plan
- Creators
- Alberto Segre - Cornell University
- Resource Type
- Journal article
- Publication Details
- Robotics and autonomous systems, Vol.8(1), pp.93-111
- Publisher
- Elsevier B.V
- DOI
- 10.1016/0921-8890(91)90016-E
- ISSN
- 0921-8890
- eISSN
- 1872-793X
- Language
- English
- Date published
- 1991
- Academic Unit
- Nursing; Fraternal Order of Eagles Diabetes Research Center; Computer Science
- Record Identifier
- 9984259420202771
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