play hide-and-seek
Why teaching robots to play hide-and-seek could be the key to next-gen A.I.
Artificial general intelligence, the idea of an intelligent A.I. agent that's able to understand and learn any intellectual task that humans can do, has long been a component of science fiction. As A.I. gets smarter and smarter -- especially with breakthroughs in machine learning tools that are able to rewrite their code to learn from new experiences -- it's increasingly widely a part of real artificial intelligence conversations as well. But how do we measure AGI when it does arrive? Over the years, researchers have laid out a number of possibilities. The most famous remains the Turing Test, in which a human judge interacts, sight unseen, with both humans and a machine, and must try and guess which is which.
Why Scientists are Teaching Robots to Play Hide-and-Seek
Artificial general intelligence, the idea of an intelligent A.I. agent that's able to understand and learn any intellectual task that humans can do, has long been a component of science fiction. As A.I. gets smarter and smarter -- especially with breakthroughs in machine learning tools that are able to rewrite their code to learn from new experiences -- it's increasingly widely a part of real artificial intelligence conversations as well. But how do we measure AGI when it does arrive? Over the years, researchers have laid out a number of possibilities. The most famous remains the Turing Test, in which a human judge interacts, sight unseen, with both humans and a machine, and must try and guess which is which.
AI Learned to Play Hide-and-Seek Using Machine Learning
OpenAI announced its new project in which an AI can learn to play hide and seek. Utilizing the Machine learning language, you can play hide and seek with AI. Initially, a simple version of the game will be released in which'Seekers' will score when a'Hider' is visible to the field. At the start of the game, the'Hider' will be given some time to set up a place for hiding. To add the pinch of interest and fun in the game, 'Seekers' and'Hiders' both can move any object over the field say walls and blocks, to take a lead over others.
OpenAI Tried to Train AI Agents to Play Hide-And-Seek but Instead They Were Shocked by What They Learned
Competition is one of the socio-economic dynamics that has influenced our evolutions as species. The vast amount of complexity and diversity on Earth evolved due to co-evolution and competition between organisms, directed by natural selection. By competing against a different party, we are constantly forced to improve our knowledge and skills on a specific subject. Recent developments in artificial intelligence(AI) have started to leverage some of the principles of competition to influence learning behaviors in AI agents. Specifically, the field of multi-agent reinforcement learning(MARL) has been heavily influenced by the competitive and game-theoretic dynamics.
An AI learned to play hide-and-seek. The strategies it came up with on its own were astounding.
This week, leading AI lab OpenAI released their latest project: an AI that can play hide-and-seek. It's the latest example of how, with current machine learning techniques, a very simple setup can produce shockingly sophisticated results. The AI agents play a very simple version of the game, where the "seekers" get points whenever the "hiders" are in their field of view. The "hiders" get a little time at the start to set up a hiding place and get points when they've successfully hidden themselves; both sides can move objects around the playing field (like blocks, walls, and ramps) for an advantage. The results from this simple setup were quite impressive.