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IJCAI
2003
9 years 12 days ago
Approximate Policy Iteration using Large-Margin Classifiers
We present an approximate policy iteration algorithm that uses rollouts to estimate the value of each action under a given policy in a subset of states and a classifier to general...
Michail G. Lagoudakis, Ronald Parr
AAAI
2006
9 years 13 days ago
Incremental Least Squares Policy Iteration for POMDPs
We present a new algorithm, called incremental least squares policy iteration (ILSPI), for finding the infinite-horizon stationary policy for partially observable Markov decision ...
Hui Li, Xuejun Liao, Lawrence Carin
SEC
2008
9 years 14 days ago
Negotiation of Prohibition: An Approach Based on Policy Rewriting
Abstract. In recent security architectures, it is possible that the security policy is not evaluated in a centralized way but requires negotiation between the subject who is reques...
Nora Cuppens-Boulahia, Frédéric Cupp...
IM
2007
9 years 14 days ago
Issues in Designing a Policy Language for Distributed Management of IT Infrastructures
— The objectives of this paper are twofold. First, we introduce a novel policy language, called CIM-SPL (Simple Policy Language for CIM) that complies with the CIM (Common Inform...
Dakshi Agrawal, Seraphin B. Calo, Kang-Won Lee, Jo...
DBSEC
2010
126views Database» more  DBSEC 2010»
9 years 15 days ago
Mining Likely Properties of Access Control Policies via Association Rule Mining
Abstract. Access control mechanisms are used to control which principals (such as users or processes) have access to which resources based on access control policies. To ensure the...
JeeHyun Hwang, Tao Xie, Vincent C. Hu, Mine Altuna...
AAAI
2010
9 years 15 days ago
Relative Entropy Policy Search
Policy search is a successful approach to reinforcement learning. However, policy improvements often result in the loss of information. Hence, it has been marred by premature conv...
Jan Peters, Katharina Mülling, Yasemin Altun
CCS
2008
ACM
9 years 1 months ago
User-controllable learning of security and privacy policies
Studies have shown that users have great difficulty specifying their security and privacy policies in a variety of application domains. While machine learning techniques have succ...
Patrick Gage Kelley, Paul Hankes Drielsma, Norman ...
ATAL
2008
Springer
9 years 1 months ago
Sigma point policy iteration
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...
WSC
2007
9 years 1 months ago
A hybrid inventory control system approach applied to the food industry
The appropriate production and inventory control policy is a key factor for modern enterprises’ success in competitive environment. In the food industry, most of food manufactur...
David Claudio, Jie Zhang, Ying Zhang
AIPS
2010
9 years 1 months ago
When Policies Can Be Trusted: Analyzing a Criteria to Identify Optimal Policies in MDPs with Unknown Model Parameters
Computing a good policy in stochastic uncertain environments with unknown dynamics and reward model parameters is a challenging task. In a number of domains, ranging from space ro...
Emma Brunskill
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