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» Approximate Policy Iteration with a Policy Language Bias
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AAAI
2006
13 years 8 months ago
Improving Approximate Value Iteration Using Memories and Predictive State Representations
Planning in partially-observable dynamical systems is a challenging problem, and recent developments in point-based techniques such as Perseus significantly improve performance as...
Michael R. James, Ton Wessling, Nikos A. Vlassis
JMLR
2006
143views more  JMLR 2006»
13 years 7 months ago
Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation
We study a sequential variance reduction technique for Monte Carlo estimation of functionals in Markov Chains. The method is based on designing sequential control variates using s...
Rémi Munos
WMCSA
2002
IEEE
14 years 8 days ago
Extensible Adaptation via Constraint Solving
Applications running on a mobile and wireless devices must be able to adapt gracefully to limited and fluctuating network resources. The variety of applications, platforms upon w...
Yuri Dotsenko, Eyal de Lara, Dan S. Wallach, Willy...
CCS
2011
ACM
12 years 7 months ago
Policy auditing over incomplete logs: theory, implementation and applications
We present the design, implementation and evaluation of an algorithm that checks audit logs for compliance with privacy and security policies. The algorithm, which we name reduce,...
Deepak Garg, Limin Jia, Anupam Datta
RSS
2007
176views Robotics» more  RSS 2007»
13 years 8 months ago
Active Policy Learning for Robot Planning and Exploration under Uncertainty
Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...