Real-world robotics: Learning to plan for robust execution-Reference-Cited by-同舟云学术

Real-world robotics: Learning to plan for robust execution

Published:1996 Issue:2-3 Volume:23 Page:121-161
ISSN:0885-6125
Container-title:Machine Learning
language:en
Short-container-title:Mach Learn

Author:

Bennett Scott W.,Dejong Gerald F.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/content/pdf/10.1007/BF00117442.pdf

Reference27 articles.

1. Agre, P. & Chapman, D. (1987). Pengi: An implementation of a theory of activity. In Proceedings of the National Conference on Artificial Intelligence, pages 268?272.

2. Bennett, S.W. (1989). Learning uncertainty tolerant plans through approximation in complex domains. Master's thesis, University of Illinois at Urbana-Champaign.

3. Brooks, R.A. (1982). Symbolic error analysis and robot planning. Technical Report 685, MIT AI Lab.

4. Brooks, R.A. (1987). Planning is just a way of avoiding figuring out what to do next. Technical Report 303, MIT AI Lab.

5. Chapman, D. (1987). Planning for conjunctive goals. Artificial Intelligence, 32(3):333?378.

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. iFALCON: A neural architecture for hierarchical planning;Neurocomputing;2012-06

2. A Brain-Inspired Model of Hierarchical Planner;2011 International Conference on Technologies and Applications of Artificial Intelligence;2011-11

3. An integrated approach of learning, planning, and execution;Journal of Intelligent and Robotic Systems;2000

4. Learning situation-dependent costs: Improving planning from probabilistic robot execution;Robotics and Autonomous Systems;1999-11