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» Local Search Algorithms for SAT: An Empirical Evaluation
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AAAI
1998
13 years 8 months ago
Learning Evaluation Functions for Global Optimization and Boolean Satisfiability
This paper describes STAGE, a learning approach to automatically improving search performance on optimization problems.STAGElearns an evaluation function which predicts the outcom...
Justin A. Boyan, Andrew W. Moore
AIPS
2004
13 years 8 months ago
A Lookahead Strategy for Heuristic Search Planning
The planning as heuristic search framework, initiated by the planners ASP from Bonet, Loerincs and Geffner, and HSP from Bonet and Geffner, lead to some of the most performant pla...
Vincent Vidal
CP
1997
Springer
13 years 11 months ago
Five Pitfalls of Empirical Scheduling Research
A number of pitfalls of empirical scheduling research are illustrated using real experimental data. These pitfalls, in general, serve to slow the progress of scheduling research b...
J. Christopher Beck, Andrew J. Davenport, Mark S. ...
APWEB
2008
Springer
13 years 9 months ago
SemSearch: A Scalable Semantic Searching Algorithm for Unstructured P2P Network
Resource searching in the current peer-to-peer (P2P) applications is mainly based on the keyword match. However, more and more P2P applications require an efficient semantic search...
Wei Song, Ruixuan Li, Zhengding Lu, Mudar Sarem
AIPS
2006
13 years 8 months ago
Optimal STRIPS Planning by Maximum Satisfiability and Accumulative Learning
Planning as satisfiability (SAT-Plan) is one of the best approaches to optimal planning, which has been shown effective on problems in many different domains. However, the potenti...
Zhao Xing, Yixin Chen, Weixiong Zhang