2017년 7월 11일 화요일

Google DeepMind AI learns to creatively move around obstacles



Reinforcement learning (RL) is the practice of teaching and guiding behavior by using a reward system. Desirable behavior produces rewards; undesirable behavior does not. It's a common tool used in machine learning, and now the the Alphabet team has used it to teach the DeepMind AI to successfully navigate a parkour course.
The team wanted to see if simple rewards would work in a complex environment. They set up a virtual parkour course with drops, hurdles and ledges and set a reward for forward progress. At its most basic level, the system was as follows: the faster the AI moved across the terrain, the greater the rewards. Additional incentives and penalties were added for more complex programs.




All of the stick figure's navigation was taught via reinforcement learning. The AI used a trial and error system to figure out how to move forward as fast as possible without "terminating."




It's clear that DeepMind is using creative solutions to get around the obstacles it's presented with; much of the time, the movement that provides the most efficient solution isn't exactly natural looking. It presents interesting possibilities for future AI because robots don't actually have to restrict themselves to human-like movements in order to accomplish set goals. It will be interesting to see if this has an effect on future AI and robot development.

모자만 쓰면 음악 감상과 통화 가능 Zeroi 킥 스타터 등록

이어폰을 착용하다 보면 아무리 착용감이 좋다 하더라도 귀가 아프거나 이질감이 들기 마련이다. 그리고 장시간 음악감상시에는 청력감소나 난청등 부작용도 있을 수 있는데 이런 단점들을 개선한 Zeroi가 킥 스타터에 등록돼 화제가 돼고 있다. Ze...