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NIPS
2007
15 years 6 months ago
Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods
Learning in real-world domains often requires to deal with continuous state and action spaces. Although many solutions have been proposed to apply Reinforcement Learning algorithm...
Alessandro Lazaric, Marcello Restelli, Andrea Bona...
SEC
2007
15 years 6 months ago
Extending Role Based Access Control Model for Distributed Multidomain Applications
This paper presents the results related to the development of a flexible domain-based access control infrastructure for distributed Grid-based Collaborative Environments and Comple...
Yuri Demchenko, Leon Gommans, Cees de Laat
IJCAI
2001
15 years 5 months ago
Complexity of Probabilistic Planning under Average Rewards
A general and expressive model of sequential decision making under uncertainty is provided by the Markov decision processes (MDPs) framework. Complex applications with very large ...
Jussi Rintanen
NIPS
1998
15 years 5 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore
IM
1997
15 years 5 months ago
The Hollowman: An Innovative ATM Control Architecture
The current implementation of out-of-band control in ATM networks inhibits their successful exploitation. The confusion in signalling protocols between application services and th...
Sean Rooney