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IJCAI
2001
13 years 11 months ago
The Exponentiated Subgradient Algorithm for Heuristic Boolean Programming
Boolean linear programs (BLPs) are ubiquitous in AI. Satisfiability testing, planning with resource constraints, and winner determination in combinatorial auctions are all example...
Dale Schuurmans, Finnegan Southey, Robert C. Holte
GECCO
2009
Springer
146views Optimization» more  GECCO 2009»
14 years 4 months ago
Analyzing the landscape of a graph based hyper-heuristic for timetabling problems
Hyper-heuristics can be thought of as “heuristics to choose heuristics”. They are concerned with adaptively finding solution methods, rather than directly producing a solutio...
Gabriela Ochoa, Rong Qu, Edmund K. Burke
AIPS
2008
14 years 9 days ago
Learning Relational Decision Trees for Guiding Heuristic Planning
The current evaluation functions for heuristic planning are expensive to compute. In numerous domains these functions give good guidance on the solution, so it worths the computat...
Tomás de la Rosa, Sergio Jiménez, Da...
ENTCS
2006
136views more  ENTCS 2006»
13 years 10 months ago
Adaptive Application of SAT Solving Techniques
New heuristics and strategies have enabled major advancements in SAT solving in recent years. However, experimentation has shown that there is no winning solution that works in al...
Ohad Shacham, Karen Yorav
EOR
2007
158views more  EOR 2007»
13 years 10 months ago
A graph-based hyper-heuristic for educational timetabling problems
This paper presents an investigation of a simple generic hyper-heuristic approach upon a set of widely used constructive heuristics (graph coloring heuristics) in timetabling. Wit...
Edmund K. Burke, Barry McCollum, Amnon Meisels, Sa...