Khaluf Yara, Simoens Pieter, Hamann Heiko
IDLab, Ghent University-Imec, Ghent, Belgium.
Institute of Computer Engineering, University of Lübeck, Lübeck, Germany.
Front Robot AI. 2019 Mar 26;6:16. doi: 10.3389/frobt.2019.00016. eCollection 2019.
Autonomous decision-making is a fundamental requirement for the intelligent behavior of individual agents and systems. For artificial systems, one of the key design prerequisites is providing the system with the ability to make proper decisions. Current literature on collective artificial systems designs decision-making mechanisms inspired mostly by the successful natural systems. Nevertheless, most of the approaches focus on voting mechanisms and miss other fundamental aspects. In this paper, we aim to draw attention to the missed pieces for the design of efficient collective decision-making, mainly information processes in its two types of stimuli and options set.
自主决策是个体智能体和系统智能行为的基本要求。对于人工系统而言，关键设计前提之一是赋予系统做出恰当决策的能力。当前关于集体人工系统的文献主要借鉴成功的自然系统来设计决策机制。然而，大多数方法聚焦于投票机制，而忽略了其他基本方面。在本文中，我们旨在提请注意高效集体决策设计中被遗漏的部分，主要是其两种刺激类型和选项集方面的信息过程。
