Protein Secondary Structure Prediction through a Cooperative MultiAgent Learning Approach
ADDIS, ANDREA;ARMANO, GIULIANO;MASCIA, FRANCESCO;VARGIU, ELOISA
2007-01-01
Abstract
This paper illustrates a cooperative multiagent learning approach devised to perform classification or prediction tasks. The resulting system is composed by a population of agents that cooperate and interact in accordance with generic requirements imposed by the adoption of evolutionary computation strategies. As a case study, we consider the typical bioinformatics problem of predicting protein secondary structure.Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.