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» Iterative Learning of Weighted Rule Sets for Greedy Search
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AIPS
2010
13 years 4 months ago
Iterative Learning of Weighted Rule Sets for Greedy Search
Greedy search is commonly used in an attempt to generate solutions quickly at the expense of completeness and optimality. In this work, we consider learning sets of weighted actio...
Yuehua Xu, Alan Fern, Sung Wook Yoon
ECAI
2008
Springer
13 years 6 months ago
Structure Learning of Markov Logic Networks through Iterated Local Search
Many real-world applications of AI require both probability and first-order logic to deal with uncertainty and structural complexity. Logical AI has focused mainly on handling com...
Marenglen Biba, Stefano Ferilli, Floriana Esposito
ILP
2003
Springer
13 years 9 months ago
Disjunctive Learning with a Soft-Clustering Method
In the case of concept learning from positive and negative examples, it is rarely possible to find a unique discriminating conjunctive rule; in most cases, a disjunctive descripti...
Guillaume Cleuziou, Lionel Martin, Christel Vrain
ESANN
2003
13 years 5 months ago
Improving iterative repair strategies for scheduling with the SVM
The resource constraint project scheduling problem (RCPSP) is an NP-hard benchmark problem in scheduling which takes into account the limitation of resources’ availabilities in ...
Kai Gersmann, Barbara Hammer
CSCLP
2008
Springer
13 years 6 months ago
From Rules to Constraint Programs with the Rules2CP Modelling Language
In this paper, we present a rule-based modelling language for constraint programming, called Rules2CP. Unlike other modelling languages, Rules2CP adopts a single knowledge represen...
François Fages, Julien Martin