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| Autore: |
Asirvatham David
|
| Titolo: |
Evolutionary Artificial Intelligence : Proceedings of ICEAI 2024 / / edited by David Asirvatham, Klimis Ntalianis, Przemyslaw Falkowski-Gilski
|
| Pubblicazione: | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
| Edizione: | 1st ed. 2025. |
| Descrizione fisica: | 1 online resource (861 pages) |
| Disciplina: | 006.3 |
| Soggetto topico: | Computational intelligence |
| Artificial intelligence | |
| Image processing - Digital techniques | |
| Computer vision | |
| Signal processing | |
| Algorithms | |
| Computational Intelligence | |
| Artificial Intelligence | |
| Computer Imaging, Vision, Pattern Recognition and Graphics | |
| Signal, Speech and Image Processing | |
| Altri autori: |
NtalianisKlimis
Falkowski-GilskiPrzemyslaw
|
| Sommario/riassunto: | This book gathers a collection of selected works and new research results of scholars and graduate students presented at International Conference on Evolutionary Artificial Intelligence (ICEAI 2024) held in Malaysia during November 26–27, 2024. The focus of the book is interdisciplinary in nature and includes research on all aspects of evolutionary computation to find effective solutions to a wide range of computationally difficult problems. The book covers topics such as particle swarm optimization, evolutionary programming, genetic programming, hybrid evolutionary algorithms, ant colony optimization, evolutionary neural networks, evolutionary reinforcement learning, genetic algorithms, memetic algorithms, novel bio-inspired algorithms, evolving multi-agent systems, agent-based evolutionary approaches, and evolutionary game theory. |
| Titolo autorizzato: | Evolutionary Artificial Intelligence ![]() |
| ISBN: | 9789819652105 |
| 9789819652099 | |
| Formato: | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9911018753303321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |