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AIMSA
2008
Springer
15 years 9 months ago
A Hybrid Approach to Distributed Constraint Satisfaction
We present a hybrid approach to Distributed Constraint Satisfaction which combines incomplete, fast, penalty-based local search with complete, slower systematic search. Thus, we pr...
David Lee, Inés Arana, Hatem Ahriz, Kit-Yin...
CORR
2002
Springer
132views Education» more  CORR 2002»
15 years 7 months ago
Robust Feature Selection by Mutual Information Distributions
Mutual information is widely used in artificial intelligence, in a descriptive way, to measure the stochastic dependence of discrete random variables. In order to address question...
Marco Zaffalon, Marcus Hutter
ECML
2007
Springer
16 years 1 months 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
NIPS
2008
15 years 8 months ago
Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms
Policy gradient (PG) reinforcement learning algorithms have strong (local) convergence guarantees, but their learning performance is typically limited by a large variance in the e...
John W. Roberts, Russ Tedrake
LEGE
2004
169views Education» more  LEGE 2004»
15 years 8 months ago
Building Assessment Web Service from Question Type Learning Objects
In this paper we discuss the TestTool system as an established testing system model, the one that is being used in real educational settings and supports self-assessment as well as...
Vytautas Reklaitis, Kazys Baniulis, Nerijus Auksta...