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» Learning Teleoreactive Logic Programs from Problem Solving
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JMLR
2012
13 years 4 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»
15 years 3 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
15 years 2 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
15 years 2 days 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»
15 years 7 months 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