Agent-based evolutionary search / / Ruhul Amin Sarker and Tapabrata Ray (Eds.)
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| Titolo: |
Agent-based evolutionary search / / Ruhul Amin Sarker and Tapabrata Ray (Eds.)
|
| Pubblicazione: | Berlin ; ; Heidelberg, : Springer-Verlag, c2010 |
| Edizione: | 1st ed. 2013. |
| Descrizione fisica: | 1 online resource (X, 206 p.) |
| Disciplina: | 006.3 |
| Soggetto topico: | Multiagent systems |
| Evolutionary computation | |
| Computer algorithms | |
| Altri autori: |
SarkerRuhul A
RayTapabrata
|
| Note generali: | Bibliographic Level Mode of Issuance: Monograph |
| Nota di bibliografia: | Includes bibliographical references and index. |
| Nota di contenuto: | 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. |
| Sommario/riassunto: | 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 several well-known specialists to present their solutions, tools, and models falling under the common denominator of the agent-based optimization. The book consists of eight chapters covering examples of application of the multi-agent paradigm and respective customized tools to solve difficult optimization problems arising in different areas such as machine learning, scheduling, transportation and, more generally, distributed and cooperative problem solving. |
| Titolo autorizzato: | Agent-based evolutionary search |
| ISBN: | 9783642340970 |
| 3642340970 | |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910438048503321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |
Serie:
Studies in Computational Intelligence, . 1860-949X ; ; 456