With the rapid development of robot technology, and opportunities for human robots to work together more and more, then, how to achieve better collaboration robots and humans do?
The autonomous robot performs a joint task and continuously sends updated task dynamics to each other: "I have already passed this gate, I am turning 90 degrees to the right for a turn." "I came across a wall and pushed 2 feet. Rotate right 90 degrees." "I came across a wall and pushed 4 feet."
Of course, as long as they need it, the computer has no problem submitting text messages over long distances. However, such data barriers will drive people crazy.
Last weekend, at the annual annual AI (Artificial Intelligence) Progressive Conference, researchers at the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Laboratory (CSAIL) presented a new approach to robotic collaboration that reduced communication needs by 60%. They believe that their models make it easier to design systems that allow humans to work with robots. For example, an emergency response team.
“We have not yet implemented a team of humans and robots,†said Julie Shah, an associate professor at the University of Aeronautics and Astronautics and one of the two authors of the paper. "But it's very exciting, because you can imagine: you can just reduce the number of communications by 60%, and presumably other communications are not really necessary for some people to achieve their mission in the team."
This work may be suitable for collaboration between multiple robots, but it is not suitable for collaboration between humans and robots. Communication consumes a certain amount of power, which is always a consideration for a battery-powered device, but in some cases, the cost of processing new information can lead to more serious resource loss.
In a multi-intelligent system, agents must collaborate on scientific terms in computer, electronics, or other ways, each agent must maintain a state of the current state, and some other agents need to be in the same state. These days, agents also expect the factors of likelihood in their models to be accurate. Based on these probabilities, they must decide whether to modify their behavior.
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