- Swarm Intelligence (群体智能)
群体智能作为一个新兴领域，已经成为人工智能以及经济、社会、生物等交叉学科的热点和前沿领域。群体智能是指在集体层面表现的分散的、去中心化的自组织行为。社会性昆虫或动物个体遵循简单的行为规则，就能在集体层面展现出高级的群体智能。比如蚁群、蜂群构成的复杂类社会系统，鸟群、鱼群为适应空气或海水而构成的群体迁移。群体智能不是简单的多个体的集合，而是超越个体行为的一种更高级表现，更具有鲁棒性、灵活性和经济上的优势。这种从个体行为到群体行为的演变过程往往极其复杂，以至于无法预测。我们致力于将机器学习与复杂自组织系统研究相结合，通过搭建多模态传感器系统，收集蜂群、蚁群等经由多模态（包括图像、声音、化学、身体接触等）通信机制调控的个体及群体行为数据，结合机器学习和计算机仿真，探究个体如何通过多模态通信实现自组织进而涌现协同运作、群体决策等高级功能。
Swarm intelligence, as an emerging field, has become the hot spot and frontier field of artificial intelligence as well as economic, social, biological and other interdisciplinary fields. Swarm intelligence refers to the decentralized self-organizing behaviors expressed at the collective level. Social insects or animals follow simple rules of behavior and show advanced swarm intelligence at the collective level. For instance, the complex social systems of ants and bees, and the migration of flocks of birds and fish to adapt to the air or sea. Swarm intelligence is not simply a collection of multiple individuals, but a higher performance beyond individual behavior, with more robustness, flexibility and economic advantages. The evolution from individual behavior to swarm behavior is often too complex to predict. We are interest in the combination of machine learning with complex self-organization system study. We construct multimodal sensor system to collect the data of individual and swarm behavior that regulated by multimodal (including images, sound, chemical, and physical contact, etc.) communication mechanisms, employ machine learning and computer simulation, to explore how the individual multimodal communication to achieve self-organization and emerging synergy, group decision-making and other advanced features.
