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» Composing and combining policies under the policy machine
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ECML
2006
Springer
15 years 9 months ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....
HPDC
2000
IEEE
15 years 10 months ago
Evaluation of Task Assignment Policies for Supercomputing Servers: The Case for Load Unbalancing and Fairness
While the MPP is still the most common architecture in supercomputer centers today, a simpler and cheaper machine configuration is growing increasingly common. This alternative s...
Bianca Schroeder, Mor Harchol-Balter
POLICY
2004
Springer
15 years 11 months ago
A Decentralized Treatment of a Highly Distributed Chinese-Wall Policy
Access control (AC) technology has come a long way from its roots as the means for sharing resources between processes running on a single machine, to a mechanism for regulating t...
Naftaly H. Minsky
CSFW
2010
IEEE
15 years 9 months ago
Towards Quantitative Analysis of Proofs of Authorization: Applications, Framework, and Techniques
—Although policy compliance testing is generally treated as a binary decision problem, the evidence gathered during the trust management process can actually be used to examine t...
Adam J. Lee, Ting Yu
ECML
2007
Springer
16 years 7 days ago
Policy Gradient Critics
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
Daan Wierstra, Jürgen Schmidhuber