Jan 7, 2018 06:32 AM
https://spectrum.ieee.org/robotics/artif...s-poachers
EXCERPT: Every year, poachers kill about 27,000 African elephants—an astounding 8 percent of the population. If current trends continue, these magnificent animals could be gone within a decade.
The solution, of course, is to stop poachers before they strike, but how to do that has long confounded authorities. In protected areas like wildlife preserves, elephants and other endangered animals may roam far and wide, while rangers can patrol only a small area at any time. “It’s a two-part problem,” explains Milind Tambe, a computer scientist at the University of Southern California, in Los Angeles. “Can you predict where poaching will happen? And can you [target] your patrols so that they’re unpredictable, so that the poachers don’t know the rangers are coming?”
To solve both parts of the problem, Tambe and his team created an artificial-intelligence system called PAWS, which stands for Protection Assistant for Wildlife Security. A machine-learning algorithm uses data from past patrols to predict where poaching is likely to occur in the future. And a game-theory model helps generate randomized, unpredictable patrol routes. The system has been field-tested [...] with good results....
MORE: https://spectrum.ieee.org/robotics/artif...s-poachers
EXCERPT: Every year, poachers kill about 27,000 African elephants—an astounding 8 percent of the population. If current trends continue, these magnificent animals could be gone within a decade.
The solution, of course, is to stop poachers before they strike, but how to do that has long confounded authorities. In protected areas like wildlife preserves, elephants and other endangered animals may roam far and wide, while rangers can patrol only a small area at any time. “It’s a two-part problem,” explains Milind Tambe, a computer scientist at the University of Southern California, in Los Angeles. “Can you predict where poaching will happen? And can you [target] your patrols so that they’re unpredictable, so that the poachers don’t know the rangers are coming?”
To solve both parts of the problem, Tambe and his team created an artificial-intelligence system called PAWS, which stands for Protection Assistant for Wildlife Security. A machine-learning algorithm uses data from past patrols to predict where poaching is likely to occur in the future. And a game-theory model helps generate randomized, unpredictable patrol routes. The system has been field-tested [...] with good results....
MORE: https://spectrum.ieee.org/robotics/artif...s-poachers