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» Learning Teleoreactive Logic Programs from Problem Solving
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JMLR
2012
11 years 9 months ago
Marginal Regression For Multitask Learning
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...
Mladen Kolar, Han Liu
ATMOS
2007
177views Optimization» more  ATMOS 2007»
13 years 9 months ago
Approximate dynamic programming for rail operations
Abstract. Approximate dynamic programming offers a new modeling and algorithmic strategy for complex problems such as rail operations. Problems in rail operations are often modeled...
Warren B. Powell, Belgacem Bouzaïene-Ayari
AI
2007
Springer
13 years 7 months ago
Learning action models from plan examples using weighted MAX-SAT
AI planning requires the definition of action models using a formal action and plan description language, such as the standard Planning Domain Definition Language (PDDL), as inp...
Qiang Yang, Kangheng Wu, Yunfei Jiang
LPAR
2010
Springer
13 years 5 months ago
Semiring-Induced Propositional Logic: Definition and Basic Algorithms
In this paper we introduce an extension of propositional logic that allows clauses to be weighted with values from a generic semiring. The main interest of this extension is that ...
Javier Larrosa, Albert Oliveras, Enric Rodrí...
EH
2003
IEEE
100views Hardware» more  EH 2003»
14 years 20 days ago
Learning for Evolutionary Design
This paper describes a technique for evolving similar solutions to similar configuration design problems. Using the configuration design of combination logic circuits as a testb...
Sushil J. Louis