Results 31 to 40 of about 28,161 (297)

Beyond swarm intelligence: the ultraswarm

Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005., 2005
This paper explores the idea that it may be possible to combine two ideas - UAV flocking, and wireless cluster computing - in a single system, the UltraSwarm. The possible advantages of such a system are considered, and solutions to some of the technical problems are identified. Initial work on constructing such a system based around miniature electric
Holland, Owen, Woods, John, De Nardi, Renzo, Clarck, Adrian   +3 more
openaire   +2 more sources

Evolutionary optimization for risk-aware heterogeneous multi-agent path planning in uncertain environments

Frontiers in Robotics and AI
Cooperative multi-agent systems make it possible to employ miniature robots in order to perform different experiments for data collection in wide open areas to physical interactions with test subjects in confined environments such as a hive.
Fatemeh Rekabi Bana, Tomáš Krajník, Farshad Arvin   +2 more
doaj   +1 more source

Emergence measurement of robot swarm intelligence based on swarm entropy

智能科学与技术学报, 2022
Swarm behavior can often produce value and complexity far beyond individual behavior.In order to more effectively derive swarm intelligence on the basis of individual intelligence, it is necessary to scientifically measure the level of swarm intelligence
Pu FENG, Wenjun WU, Jie LUO, Xin YU, Yongkai TIAN   +4 more
doaj  

A Hybrid of Fully Informed Particle Swarm and Self-Adaptive Differential Evolution for Global Optimization

Applied Sciences, 2022
Evolutionary computation algorithms (EC) and swarm intelligence have been widely used to solve global optimization problems. The optimal solution for an optimization problem is called by different terms in EC and swarm intelligence.
Shir Li Wang, Sarah Hazwani Adnan, Haidi Ibrahim, Theam Foo Ng, Parvathy Rajendran   +4 more
doaj   +1 more source

A Diversity Model Based on Dimension Entropy and Its Application to Swarm Intelligence Algorithm

Entropy, 2021
The swarm intelligence algorithm has become an important method to solve optimization problems because of its excellent self-organization, self-adaptation, and self-learning characteristics.
Hongwei Kang, Fengfan Bei, Yong Shen, Xingping Sun, Qingyi Chen   +4 more
doaj   +1 more source

Orthogonal learning particle swarm optimization [PDF]

, 2010
Particle swarm optimization (PSO) relies on its learning strategy to guide its search direction. Traditionally, each particle utilizes its historical best experience and its neighborhood’s best experience through linear summation.
Zhi-hui Zhan, Jun Zhang, Yu-hui Shi, Zhan, Z-H., Yun Li, Li, Y., Shi, Y-H., Zhang, J.   +7 more
core   +1 more source

Swarm Intelligence

CoRR, 2009
info:eu-repo/semantics ...
Doerner, Karl, Merkle, Daniel, Stützle, Thomas   +2 more
  +6 more sources

Human experience-guided reinforcement learning for carrier-based aircraft support operation scheduling

Defence Technology
The efficiency of carrier-based aircraft support operation scheduling critically impacts aircraft carrier operational effectiveness by determining sortie generation rates, yet faces significant challenges in complex deck environments characterized by ...
Xudong Chen, Yizhe Luo, Qihang Sun, Wenxiao Guo, Zhao Jin, Shuo Feng, Yucheng Shi, Mingliang Xu   +7 more
doaj   +1 more source

Resilient bipartite tracking control for multi-quadrotor systems with semi-markov switching topologies: Theory and experiment

Defence Technology
Quadrotors depend on efficient swarm control enabled by frequent information exchange to track a non-cooperative target. However, communication disruptions including attacks or random link variations in complex environments, jeopardize mission success ...
Lin Sun, Juntong Qi, Liyuan Sun, Mingming Wang, Yan Peng, Hailong Huang   +5 more
doaj   +1 more source

Organizing the interface—Plasma membrane architecture and receptor dynamics in virus‐cell interactions

FEBS Letters, EarlyView.
Plasma membranes contain dynamic nanoscale domains that organize lipids and receptors. Because viruses operate at similar scales, this architecture shapes early infection steps, including attachment, receptor engagement, and entry. Using influenza A virus and HIV‐1 as examples, we highlight how receptor nanoclusters, multivalent glycan interactions ...
Jan Schlegel, Christian Sieben
wiley   +1 more source