The biological principles of swarm intelligence

By Simon Garnier, Jacques Gautrais, Guy Theraulaz. Swarm Intelligence, 2007

579 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Computer Networks and Communications, Genetics

View Paper: https://www.semanticscholar.org/paper/0a51ba5028fd500965d82a2149647b18b5932f99

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cellular and Molecular Neuroscience

1. Heitor Silvério Lopes
2. Rafael Stubs Parpinelli

In Computer Networks and Communications

1. Ying Tan
2. Paolo Rocca
3. Andrea Massa
4. Marco Dorigo
5. Michael Bonani
6. Francesco Mondada
7. Heitor Silvério Lopes
8. Zhongyang Zheng

In Genetics

1. Ying Tan
2. Marco Dorigo
3. Michael Bonani
4. Francesco Mondada
5. Shervin Nouyan
6. Zhongyang Zheng
7. Roderich Groß

Citations in the corpus

• Evolutionary optimization as applied to inverse scattering problems (2009, methodology): “Like PSO, the ACO is based on the concepts of swarm intelligence and cooperation, but it also exploits the paradigm of stigmergy and self-organization [64].”
• Teamwork in Self-Organized Robot Colonies (2009, background): “The general paradigm is often referred to as swarm intelligence [14], [19], [25].”
• New inspirations in swarm intelligence: a survey (2011, background): “Emergent behaviour is a property that emerges through local interactions among system components and it is not possible to be achieved by any of the components of the system acting alone (Bonabeau et al., 1999; Garnier et al., 2007).”
• Research Advance in Swarm Robotics (2013, background): “[22] Garnier S, Gautrais J, Theraulaz G.”
• Swarm Robotic Behaviors and Current Applications (2020, background): “Moreover, Garnier et al. (2007) provide a good overview of the biological principles of swarm intelligence.”
• Fireworks Algorithm for Optimization (2010, background): “In recent years, Swarm Intelligence (SI) has become popular among researchers working on optimization problems all over the world [1,2].”
• A novel collaborative optimization algorithm in solving complex optimization problems (2016, background): “…2012) [genetic algorithm (GA), evolutionary programming (EP), differential evolution (DE), etc.], swarm intelligence optimization algorithms (Garnier et al. 2007; Wen et al. 2015) [ant colony optimiza-123 tion (ACO), particle swarm optimization (PSO), bee colony optimization (BCO), etc.],…”