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» MDPs: Learning in Varying Environments
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GECCO
2009
Springer
135views Optimization» more  GECCO 2009»
14 years 4 months ago
Neuroevolutionary reinforcement learning for generalized helicopter control
Helicopter hovering is an important challenge problem in the field of reinforcement learning. This paper considers several neuroevolutionary approaches to discovering robust cont...
Rogier Koppejan, Shimon Whiteson
ICML
2008
IEEE
14 years 10 months ago
Non-parametric policy gradients: a unified treatment of propositional and relational domains
Policy gradient approaches are a powerful instrument for learning how to interact with the environment. Existing approaches have focused on propositional and continuous domains on...
Kristian Kersting, Kurt Driessens
AGENTS
2001
Springer
14 years 2 months ago
Adjustable autonomy in real-world multi-agent environments
Through adjustable autonomy (AA), an agent can dynamically vary the degree to which it acts autonomously, allowing it to exploit human abilities to improve its performance, but wi...
Paul Scerri, David V. Pynadath, Milind Tambe
ICDE
2011
IEEE
258views Database» more  ICDE 2011»
13 years 1 months ago
SystemML: Declarative machine learning on MapReduce
Abstract—MapReduce is emerging as a generic parallel programming paradigm for large clusters of machines. This trend combined with the growing need to run machine learning (ML) a...
Amol Ghoting, Rajasekar Krishnamurthy, Edwin P. D....
HICSS
1999
IEEE
106views Biometrics» more  HICSS 1999»
14 years 2 months ago
Representational Support for Collaborative Inquiry
Empirical work with "Belvedere," a software environment for the construction of diagrammatic representations of evidential relations, is summarized, leading to the hypot...
Daniel D. Suthers