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      Scientists make breakthrough in AI navigational ability

      Source: Xinhua    2018-05-14 19:25:31

      LONDON, May 14 (Xinhua) -- Scientists have found ways for artificial intelligence (AI) to create navigational ability.

      An artificial agent was developed to approximate grid cells, a type of neuron in the brains of many mammal species that allows them to understand their position in space, according to a research report published last week in the journal Nature.

      By combining an artificial recurrent network with a larger network architecture, an agent was formed with a deep reinforcement learning ability to navigate itself to goals in challenging virtual reality game environments.

      "This agent performed at a super-human level ... exhibited the type of flexible navigation normally associated with animals," said scientists at the London-headquartered Deepmind.

      The study tested the theory that grid cells support vector-based navigation, enabling the mammalian brain to calculate the distance and direction to a desired destination.

      The results also reflect the philosophy that algorithms used for AI can meaningfully approximate elements of the brain.

      "In the future such networks may well provide a new way for scientists to conduct 'experiments', suggesting new theories and even complementing some of the work that is currently conducted in animals," according to Deepmind scientists.

      Acquired by Google in 2016, Deepmind is the creator of AlphaGo that is focused on machine learning.

      Editor: Li Xia
      Related News
      Xinhuanet

      Scientists make breakthrough in AI navigational ability

      Source: Xinhua 2018-05-14 19:25:31

      LONDON, May 14 (Xinhua) -- Scientists have found ways for artificial intelligence (AI) to create navigational ability.

      An artificial agent was developed to approximate grid cells, a type of neuron in the brains of many mammal species that allows them to understand their position in space, according to a research report published last week in the journal Nature.

      By combining an artificial recurrent network with a larger network architecture, an agent was formed with a deep reinforcement learning ability to navigate itself to goals in challenging virtual reality game environments.

      "This agent performed at a super-human level ... exhibited the type of flexible navigation normally associated with animals," said scientists at the London-headquartered Deepmind.

      The study tested the theory that grid cells support vector-based navigation, enabling the mammalian brain to calculate the distance and direction to a desired destination.

      The results also reflect the philosophy that algorithms used for AI can meaningfully approximate elements of the brain.

      "In the future such networks may well provide a new way for scientists to conduct 'experiments', suggesting new theories and even complementing some of the work that is currently conducted in animals," according to Deepmind scientists.

      Acquired by Google in 2016, Deepmind is the creator of AlphaGo that is focused on machine learning.

      [Editor: huaxia]
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