Paper Info
Title
An Application of Causality for Representing and Providing Formal Explanations about the Behavior of the Threshold Accepting Algorithm
Abstract
The problem of algorithm selection for solving NP problems arises with the appearance of a variety of heuristic algorithms. The first works claimed the supremacy of some algorithm for a given problem. Subsequent works revealed the supremacy of algorithms only applied to a subset of instances. However, it was not explained why an algorithm solved better a subset of instances. In this respect, this work approaches the problem of explaining through causal model the interrelations between instances characteristics and the inner workings of algorithms. For validating the results of the proposed approach, a set of experiments was carried out in a study case of the Threshold Accepting algorithm to solve the Bin Packing problem. Finally, the proposed approach can be useful for redesigning the logic of heuristic algorithms and for justifying the use of an algorithm to solve an instance subset. This information could contribute to algorithm selection for NP problems.
Year
DOI
Venue
2008
10.1007/978-3-540-69731-2_102
ICAISC
Keywords
Field
DocType
instances characteristic,threshold accepting algorithm,inner working,np problem,causal model,instance subset,providing formal explanations,algorithm selection,heuristic algorithm,bin packing problem,causal models
Causality,Algorithmics,Computer science,Artificial intelligence,Algorithm Selection,Causal model,Mathematical optimization,Heuristic,Heuristic (computer science),Algorithm,Machine learning,Bin packing problem,NP
Conference
Volume
ISSN
Citations 
5097
0302-9743
0
PageRank 
References 
Authors
0.34
8
7
Name
Order
Citations
PageRank
Joaquín Pérez1459.56
Laura Cruz28928.40
Rodolfo Pazos3192.16
Vanesa Landero410.71
Gerardo Reyes510.71
Héctor J. Fraire H.6469.52
Juan Frausto Solís73912.02