Khan Md Mohiuddin, Kasmarik Kathryn, Barlow Michael
School of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia.
Front Robot AI. 2018 Dec 18;5:134. doi: 10.3389/frobt.2018.00134. eCollection 2018.
Motivation is a crucial part of animal and human mental development, fostering competence, autonomy, and open-ended development. Motivational constructs have proved to be an integral part of explaining human and animal behavior. Computer scientists have proposed various computational models of motivation for artificial agents, with the aim of building artificial agents capable of autonomous goal generation. Multi-agent systems and swarm intelligence are natural extensions to the individual agent setting. However, there are only a few works that focus on motivation theories in multi-agent or swarm settings. In this study, we review current computational models of motivation settings, mechanisms, functions and evaluation methods and discuss how we can produce systems with new kinds of functions not possible using individual agents. We describe in detail this open area of research and the major research challenges it holds.
动机是动物和人类心理发展的关键部分，促进能力、自主性和开放式发展。动机结构已被证明是解释人类和动物行为的一个不可或缺的部分。计算机科学家已经为智能体提出了各种动机计算模型，目的是构建能够自主生成目标的智能体。多智能体系统和群体智能是个体智能体设置的自然扩展。然而，只有少数作品关注多智能体或群体环境中的动机理论。在本研究中，我们回顾了当前动机设置、机制、功能和评估方法的计算模型，并讨论了如何能够生产出具有单个智能体无法实现的新功能的系统。我们详细描述了这个开放的研究领域及其面临的主要研究挑战。
