Survey of Swarm Intelligence Algorithms
| Autor: | Eunmi Choi, Suganya Selvaraj |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Collective behavior
Computer science media_common.quotation_subject 010401 analytical chemistry 02 engineering and technology 01 natural sciences Swarm intelligence Adaptability 0104 chemical sciences Robustness (computer science) Scalability 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Simplicity Control parameters Complex problems Algorithm media_common |
| Zdroj: | ICSIM |
| DOI: | 10.1145/3378936.3378977 |
| Popis: | Swarm Intelligence (SI) is an AI technique that has the collective behavior of a decentralized, self-organized system. SI has more advantages such as scalability, adaptability, collective robustness and individual simplicity and also has the ability to solve complex problems. Besides, SI algorithms also have few issues in time-critical applications, parameter tuning, and stagnation. SI algorithms need to be studied more to overcome these kinds of issues. In this paper, we studied a few popular algorithms in detail to identify important control parameters and randomized distribution. We also studied and summarized the performance comparison of SI algorithms in different applications. |
| Databáze: | OpenAIRE |
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