Effectiveness of Synchronization and Cooperative Behavior of Multiple Robots based on Swarm AI We investigated the effectiveness of Swarm AI, which allows multiple artificial intelligence (AI) robots to autonomously collaborate and achieve more advanced functions as a group. We built two models of robot groups, each equipped with its own AI, and ran simulations. The first one showed that multiple robots can sense the situation of another party and acquire synchronous behavior by reinforcement learning. The second one clarified that the efficiency of cleaning improved by 30xe2x80x9340 % as a result of introducing cooperative behavior based on Swarm AI into the group of cleaning robots. These findings demonstrate that the cooperation of multiple robots using Swarm AI is effective.

What is A Robot Swarm: A Definition for Swarming Robotics The swarm, a type of multiagent system, has enjoyed a recent surge in popularity within the autonomous robotics field. Despite a variety of theoretical and simulated research work in the area of swarm theory and multiagent artificial intelligence, the practical use of swarms remains limited. Though many limiting factors lie on the technical front, one limiting factor may be a lack of appreciation for swarm capabilities and applications as opposed to those of conventional robotics. To help address the latter limiting factor, this paper proposes a definition of a swarm in the context of autonomous robotics, describes many realworld problems that can be addressed through use of swarms, and details current applications of swarming robotic systems.