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» Highly Adaptive Learning for All - Vision and Plan
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AIPS
2006
14 years 11 months ago
Lessons Learned in Applying Domain-Independent Planning to High-Speed Manufacturing
Much has been made of the need for academic planning research to orient towards real-world applications. In this paper, we relate our experience in adapting domain-independent pla...
Minh Binh Do, Wheeler Ruml
78
Voted
NIPS
1993
14 years 11 months ago
The Parti-Game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-Spaces
Parti-game is a new algorithm for learning feasible trajectories to goal regions in high dimensionalcontinuousstate-spaces. In high dimensions it is essential that learningdoes not...
Andrew W. Moore
CIIA
2009
14 years 10 months ago
Dynamic Scheduling in Petroleum Process using Reinforcement Learning
Petroleum industry production systems are highly automatized. In this industry, all functions (e.g., planning, scheduling and maintenance) are automated and in order to remain comp...
Nassima Aissani, Bouziane Beldjilali
IJCAI
2007
14 years 11 months ago
Online Speed Adaptation Using Supervised Learning for High-Speed, Off-Road Autonomous Driving
The mobile robotics community has traditionally addressed motion planning and navigation in terms of steering decisions. However, selecting the best speed is also important – be...
David Stavens, Gabriel Hoffmann, Sebastian Thrun
ECAI
2000
Springer
15 years 1 months ago
Continual Planning with Time-Oriented, Skeletal Plans
In dynamically changing environments a planning system does not have all the required information at the first place and the world state can change, rendering the original plan i...
Silvia Miksch, Andreas Seyfang