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ICML
2002
IEEE
14 years 10 months ago
Discovering Hierarchy in Reinforcement Learning with HEXQ
An open problem in reinforcement learning is discovering hierarchical structure. HEXQ, an algorithm which automatically attempts to decompose and solve a model-free factored MDP h...
Bernhard Hengst
ATAL
2009
Springer
14 years 4 months ago
Evaluating hybrid constraint tightening for scheduling agents
Hybrid Scheduling Problems (HSPs) combine temporal and finite-domain variables via hybrid constraints that dictate that specific bounds on temporal constraints rely on assignments...
James C. Boerkoel Jr., Edmund H. Durfee
GECCO
2005
Springer
14 years 3 months ago
Probabilistic distribution models for EDA-based GP
This paper proposes a novel technique for a program evolution based on probabilistic models. In the proposed method, two probabilistic distribution models with probabilistic depen...
Kohsuke Yanai, Hitoshi Iba
AIPS
2000
13 years 11 months ago
Distance-Based Goal-Ordering Heuristics for Graphplan
We will discuss the shortcomings of known variable and value ordering strategies for Graphplan's backward search phase, and propose a novel strategy that is based on a notion...
Subbarao Kambhampati, Romeo Sanchez Nigenda
AAAI
2007
14 years 10 days ago
Learning Graphical Model Structure Using L1-Regularization Paths
Sparsity-promoting L1-regularization has recently been succesfully used to learn the structure of undirected graphical models. In this paper, we apply this technique to learn the ...
Mark W. Schmidt, Alexandru Niculescu-Mizil, Kevin ...