Paper Info
Title
Using genetic algorithms to create solutions for conflict resolution
Abstract
The process of devising solutions for conflict resolution generally configures a challenging task. There exist different approaches to address the problem, namely the use of case-based models or even relying on the parties themselves to perform the task. From a computational point of view, these problems generally represent a NP-complete problem. In order to surpass this shortcoming, in this paper it is presented a biologically inspired method to deal with the problem in which genetic algorithms are used to create possible solutions for a given dispute. The approach presented is able to generate a broad number of diverse solutions that cover virtually the whole search space for a given problem. This approach provides better results than a case-based approach since: (1) it is independent of the legal domain and (2) it does not depend on the number and quality of cases present in a database. The results of this work are being applied in a negotiation tool that is part of the UMCourt conflict resolution platform.
Year
DOI
Venue
2013
10.1016/j.neucom.2012.03.024
Neurocomputing
Keywords
Field
DocType
computational point,broad number,challenging task,umcourt conflict resolution platform,genetic algorithm,better result,case-based model,conflict resolution,different approach,np-complete problem,case-based approach,genetic algorithms,online dispute resolution,negotiation
Computer science,Conflict resolution,Online dispute resolution,Artificial intelligence,Genetic algorithm,Machine learning,Negotiation
Journal
Volume
ISSN
Citations 
109,
0925-2312
2
PageRank 
References 
Authors
0.37
15
3
Name
Order
Citations
PageRank
Davide Carneiro123632.47
Paulo Novais2883171.45
José Neves358075.09