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Google is experimenting to see whether its game-playing AIs will learn to cooperate with each other:
When our robot overlords arrive, will they decide to kill us or cooperate with us? New research from DeepMind, Alphabet Inc.'s London-based artificial intelligence unit, could ultimately shed light on this fundamental question.
They have been investigating the conditions in which reward-optimizing beings, whether human or robot, would choose to cooperate, rather than compete. The answer could have implications for how computer intelligence may eventually be deployed to manage complex systems such as an economy, city traffic flows, or environmental policy.
Joel Leibo, the lead author of a paper DeepMind published online Thursday, said in an e-mail that his team's research indicates that whether agents learn to cooperate or compete depends strongly on the environment in which they operate.
While the research has no immediate real-world application, it would help DeepMind design artificial intelligence agents that can work together in environments with imperfect information. In the future, such work could help such agents navigate a world full of intelligent entities -- both human and machine -- whether in transport networks or stock markets.
DeepMind blog post. Also at The Verge.
(Score: 2, Interesting) by Anonymous Coward on Friday February 10 2017, @03:34PM
While the summary says there is "no immediate real-world application", some traffic flow demonstrations are starting now. On a private forum I just read comments from the:
...Program Manager of the Connected Vehicle Pilot for Client Tampa Hillsborough Expressway Authority (THEA).
This is a USDOT funded program. He goes on:
We intend to deploy 1600 private vehicles, 10 transit buses and 8 streetcars with aftermarket on board units (OBUs) and equip 40 locations in downtown business district of Tampa, FL with Roadside Units (RSUs). We will implement vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) applications to resolve identified real-world issues in the study area. These applications include forward collision warning (FCW), emergency electronic brake light warning (EEBLW), wrong way entry (WWE), intersection movement assist (IMA), intelligent traffic signal (I-SIG), intelligent pedestrian signal (PED-SIG), transit signal priority (TSP) and end of ramp deceleration warning (ERDW).
Cue to Google DeepMind -- They also plan an Android app for pedestrians to access the system.
Similar programs are funded for Wyoming and New York City. http://www.tampacvpilot.com/learn/what-were-doing/ [tampacvpilot.com]