Cambier Nicolas, Miletitch Roman, Frémont Vincent, Dorigo Marco, Ferrante Eliseo, Trianni Vito
School of Computing, University of Leeds, Leeds, United Kingdom.
IRIDIA, Université Libre de Bruxelles, Brussels, Belgium.
Front Robot AI. 2020 Feb 11;7:12. doi: 10.3389/frobt.2020.00012. eCollection 2020.
While direct local communication is very important for the organization of robot swarms, so far it has mostly been used for relatively simple tasks such as signaling robots preferences or states. Inspired by the emergence of meaning found in natural languages, more complex communication skills could allow robot swarms to tackle novel situations in ways that may not be a priori obvious to the experimenter. This would pave the way for the design of robot swarms with higher autonomy and adaptivity. The state of the art regarding the emergence of communication for robot swarms has mostly focused on offline evolutionary approaches, which showed that signaling and communication can emerge spontaneously even when not explicitly promoted. However, these approaches do not lead to complex, language-like communication skills, and signals are tightly linked to environmental and/or sensory-motor states that are specific to the task for which communication was evolved. To move beyond current practice, we advocate an approach to emergent communication in robot swarms based on language games. Thanks to language games, previous studies showed that cultural self-organization-rather than biological evolution-can be responsible for the complexity and expressive power of language. We suggest that swarm robotics can be an ideal test-bed to advance research on the emergence of language-like communication. The latter can be key to provide robot swarms with additional skills to support self-organization and adaptivity, enabling the design of more complex collective behaviors.
虽然直接的局部通信对于机器人集群的组织非常重要,但到目前为止,它主要用于相对简单的任务,如表明机器人的偏好或状态。受自然语言中意义出现的启发,更复杂的通信技能可以让机器人集群以实验者事先可能不明显的方式应对新情况。这将为设计具有更高自主性和适应性的机器人集群铺平道路。关于机器人集群通信出现的现有技术大多集中在线下进化方法上,这些方法表明,即使没有明确促进,信号传递和通信也能自发出现。然而,这些方法不会产生复杂的、类似语言的通信技能,而且信号与通信所进化出的特定任务的环境和/或感觉运动状态紧密相连。为了超越当前的实践,我们提倡一种基于语言游戏的机器人集群中涌现通信的方法。由于语言游戏,先前的研究表明,文化自组织而非生物进化可能是语言复杂性和表现力的原因所在。我们认为群体机器人学可以成为推进类似语言通信出现研究的理想试验台。后者对于为机器人集群提供支持自组织和适应性的额外技能可能至关重要,从而能够设计更复杂的集体行为。