Agent-based optimization

This volume presents a collection of original research works by leading specialists focusing on novel and promising approaches in which the multi-agent system paradigm is used to support, enhance or replace traditional approaches to solving difficult optimization problems. The editors have invited s...

Description complète

Enregistré dans:
Détails bibliographiques
Auteur principal: Czarnowski, Ireneusz (Directeur de la publication)
Autres auteurs: J©edrzejowicz, Piotr (Éditeur intellectuel, Directeur de la publication), Kacprzyk, Janusz, 1947- (Éditeur intellectuel, Directeur de la publication)
Format: Livre numérique
Langue:Anglais
Publié: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
Édition:1st ed. 2013.
Collection:Studies in Computational Intelligence 456
Accès en ligne:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Note: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Agent-Based Optimization, Texte imprimé, 9783642340963
• Agent-Based Optimization, Texte imprimé, 9783642340987
• Agent-Based Optimization, Texte imprimé, 9783642447310
• Agent-Based Optimization, Texte imprimé, 9783642340963
Table des matières:
  • Machine Learning and Multiagent Systems as Interrelated Technologies Ant Colony Optimization for the Multi-criteria Vehicle Navigation Problem Solving Instances of the Capacitated Vehicle Routing Problem Using Multi-Agent Non-Distributed and Distributed Environment Structure vs. Efficiency of the Cross-Entropy Based Population Learning Algorithm for Discrete-Continuous Scheduling with Continuous Resource Discretisation Triple-Action Agents Solving the MRCPSP/max Problem Team of A-Teams - a Study of the Cooperation Between Program Agents Solving Difficult Optimization Problems Distributed Bregman-Distance Algorithms for Min-Max Optimization A Probability Collectives Approach for Multi-Agent Distributed and Cooperative Optimization with Tolerance for Agent Failure