In this experiment the robot will solve a problem by deciding what actions it should take and in what order. The robot will be told to pour a glass of water, make it cold, and give it to a person. The robot will decide how to do this while being aware of its surroundings and its own situation.
"So far, robots, including industrial robots, have been able to do specific tasks quickly and accurately. But if their environment changes slightly, robots like that can't respond. This robot remembers only basic knowledge, and it can apply that knowledge to its immediate situation. If it doesn't know enough, it stops, and reacts by saying, "I can't do this because I don't know how." So, if you teach this robot just the things that it can't do, it incorporates those things as new knowledge, and it can solve the problem overall, by including that knowledge."
"Thinking about artificial intelligence in the real world, actual environments are inevitably more complex, and they change quickly. So it's necessary to have a learning mechanism that adapts to the situation. Also, because new situations emerge, it's also necessary to have the ability to keep learning new information on the spot.
As an algorithm for achieving that, we've created SOINN. SOINN is very light on computation, and it can learn while eliminating noise from the new information that comes in." As well as the robot's sensory information, in the form of visual, auditory, and tactile data, SOINN obtains information from other sources, including the Internet and other robots' experiences and knowledge. In this way, it gradually becomes smarter.