This paper presents a scalable decentralized multi agent framework that facilitates the exchange of information between computing units through computer networks. The architectural boundaries imposed by the tool make it suitable for collective intelligence research experiments ranging from agents that exchange hello world messages to virtual drone agents exchanging positions and eventually agents exchanging information via radio with real Crazyflie drones in VU Amsterdam laboratory. The field modulation theory is implemented to construct synthetic local perception maps for agents, which are constructed based on neighbouring agents positions and neighbouring points of interest dictated by the environment. By constraining the experimental setup to a 2D environment with discrete actions, constant velocity and parameters tailored to VU Amsterdam laboratory, UAV Crazyflie drones running hill climbing controller followed collision-free trajectories and bridged sim-to-real gap.

翻译：本文提出了一种可扩展的分布式多智能体框架，该框架通过计算机网络促进计算单元之间的信息交换。该工具所设定的架构边界使其适用于从交换"Hello World"消息的智能体，到交换位置的虚拟无人机智能体，最终扩展至阿姆斯特丹自由大学实验室中通过无线电与真实Crazyflie无人机交换信息的智能体等一系列集体智能研究实验。通过实现场调制理论，为智能体构建了基于邻近智能体位置及环境规定的邻近兴趣点的合成局部感知地图。通过将实验环境限定为二维空间，采用离散动作、恒定速度及针对阿姆斯特丹自由大学实验室定制的参数，运行爬山控制器的Crazyflie无人机实现了无碰撞轨迹飞行，并成功弥合了仿真与现实的鸿沟。