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CCGRID
2007
IEEE
14 years 3 months ago
Performance Evaluation in Grid Computing: A Modeling and Prediction Perspective
Experimental performance studies on computer systems, including Grids, require deep understandings on their workload characteristics. The need arises from two important and closel...
Hui Li
COLT
2008
Springer
13 years 10 months ago
Adaptive Aggregation for Reinforcement Learning with Efficient Exploration: Deterministic Domains
We propose a model-based learning algorithm, the Adaptive Aggregation Algorithm (AAA), that aims to solve the online, continuous state space reinforcement learning problem in a de...
Andrey Bernstein, Nahum Shimkin
NIPS
1994
13 years 10 months ago
Finding Structure in Reinforcement Learning
Reinforcement learning addresses the problem of learning to select actions in order to maximize one's performance inunknownenvironments. Toscale reinforcement learning to com...
Sebastian Thrun, Anton Schwartz
AAAI
1996
13 years 10 months ago
Integrating Grid-Based and Topological Maps for Mobile Robot Navigation
Research on mobile robot navigation has produced two major paradigms for mapping indoorenvironments: grid-based and topological. While grid-based methods produce accurate metric m...
Sebastian Thrun, Arno Bücken
WWW
2005
ACM
14 years 9 months ago
Learning domain ontologies for Web service descriptions: an experiment in bioinformatics
The reasoning tasks that can be performed with semantic web service descriptions depend on the quality of the domain ontologies used to create these descriptions. However, buildin...
Marta Sabou, Chris Wroe, Carole A. Goble, Gilad Mi...