前沿与颠覆性技术是物化新装备、形成新能力的“孵化器”，超前谋划和抢先占领战略前沿技术制高点，是武器装备创新突破的重要途径。当前，新军事革命与科技革命不断向纵深发展，正在深刻影响未来武器装备发展与作战样式变革，受到美国等世界军事强国的高度关注。作为世界军工巨头的雷声公司面向未来作战，发布了《面向未来战争——培育新兴技术》报告，提出重点培育的前沿与颠覆性技术，涉及人工智能、人机交互等11个方向。北京航天情报与信息研究所对雷声公司发布的该报告进行编译。本期对人工智能技术技术进行介绍。

　　人工智能技术 ——使机器像章鱼一样具备学习能力

　　伴随学习机器人和情感计算机的出现，人工智能将成为现实名为“宙斯”的机器蟑螂，其被广为人知的原因只有两个。一是它讨厌光。二是它能够移动其身体，尽管它不知道如何运动、不知道其拥有哪些零件。在五分钟时间内，“宙斯”学会了如何走路。15分钟内，它能够向后走。该小型机器人在运动过程中，彰显了后退有时候比向前转向更有效率。 “宙斯”的一小步后退却是研发人员取得的巨大进步。雷声公司研发专家开发的“宙斯”机器人拥有与蟑螂和章鱼类似的神经系统。研发人员创造能够思考、学习和推论的事物，包括机器类的昆虫和章鱼、模拟情感、文体教练和计算机化的教师。所有这些都是美军期待的人工智能领域的创新，也是“寻求人机匹配新方式”等美军相关计划的重要内容。

　　以光速思考人工智能是美国国防部“第三次抵消战略”的组成部分。

　　“以光速思考”的智能机器能够帮助部队制定更佳的战场决策。人工智能技术的兴起将改变飞行器的设计方式，飞行员的飞行方式以及战场信息的传递方式。

　　从简单做起

　　人工智能体现为多种形式。例如，典型的象棋机器人、智能手机私人助理、看似具有情感的视频游戏人物、自动驾驶汽车，以及如前所述的机器蟑螂“宙斯”。要实现一个拥有全面思考、推理、智能的自主系统，必须从简单做起。起初，“宙斯”采用一个功率仅为9伏的电池，装有一个简单的大脑：每半边装有三个神经元，一个通信中心（名为人工前额皮层）。之后又开发了机器人“大力士”和“雅典娜”。通过程序设置，这两种机器人均惧怕光，但增加了太阳能动力设计。当其电池电量不足时，机器人会感觉到“饥饿”，其不得不寻找光源并充电，即使感觉到光源将“伤害”它们。因此，这种机器人将不得不权衡“光源将产生伤害，但如果找不到光源将死掉”的本能。

　　带感情的行动上述本能产生了情感，这种情感是人工智能所必需的。

　　人类大脑中的整个学习系统与人的情感紧密相连。情感帮助大脑决定如何使用资源。人工智能同样需要情感，因为不论制造的人工智能系统如何强大，它拥有有限的记忆、有限的处理器、有限的动力。因此，必需考虑如何分配资源问题。诸如恐惧和忧虑等情感能够有助于人工智能系统提高生存能力。

　　文化环境仿真雷声公司的比尔费格斯实验室为美国国防高级研究计划局开发了一种视频游戏式的仿真器，该仿真器采用人工智能技术解读使用者的肢体语言，用于训练如何在国外环境中与陌生人接触，为使用者在其采取行动（如问路）之前提供有礼貌的、友好的建议。该仿真器通过卓越的人工智能程序控制视频中人物的态度和动作。

　　人工大脑控制行动机器人章鱼拥有一个主要大脑，可发布诸如“吃”或“移动”等主要命令，每条爪子上安有一个用于执行命令的独立神经包。雷声公司的目标是开发一个在中央控制单元协调下能够协同工作的机器设备网络，就像有一个真实的人在掌舵一样。例如，一个深海猎雷艇编队自主在大洋底部运行，当其发现有价值事项时才向操控人员反馈。这一编队拥有自主的防御和安全意识，操控人员成为发布任务参数的人，无需关注编队执行任务的具体过程。

　　英文原文

　　The robotic cockroach was called Zeus, and it came into the world knowing only two things.The first was that it hated light. The second was that it could move its body — though it didn’t know how, or what parts it had. Within five minutes, Zeus had learned to walk. Within 15, it could walk backwards. The little robot, searching for darkness, had figured out that backing up is sometimes more efficient than making a forward turn. Zeus’ tiny steps backward were an enormous step forward for its creator, James Crowder, one of Raytheon’s experts in the field of artificial intelligence. Their work in creating things that think, learn and reason includes mechanical versions of insects and octopuses, simulated emotions, cultural coaches and computerized versions of schoolteachers. And it all comes as the United States military looks for innovation in artificial intelligence as part of its plan to find new ways of pairing humans and machines.

　　THINKING ‘AT THE SPEED OF LIGHT’

　　Artificial intelligence is part of the Department of Defense’s “Third Offset” Strategy, a plan to give the United States military strong advantages that would deter enemies from attacking. Smart machines that “operate at the speed of light” could help troops make better battlefield decisions, Deputy Defense Secretary Bob Work said during a discussion of the Third Offset Strategy at the Reagan National Defense Forum. “So when you’re operating against a cyber-attack or an electronic warfare attack or attacks against your space architecture or missiles that are coming, screaming in at you at Mach 6,” Work said, “you’re going to have to have a learning machine that helps you solve that problem right away.” The advent of AI could change the way vehicles are designed, how pilots fly and how battlefield information is delivered, said Paul Scharre, a former U.S. Army Ranger and now a senior fellow at the Center for a New American Security. “You’re not going to eliminate people from warfare, but there are advantages to machine intelligence to augment the capacity of warfighters — the same way Google augments our ability to process information, or a smartphone,” Scharre said.

　　STARTING SIMPLE

　　Artificial intelligence takes many forms. There’s the classic chess-playing robot. The smartphone personal assistant. Seemingly sentient characters in videogames. Self-driving cars. And in Crowder’s case, there’s the cockroach. He knew if he was ever going to build a machine of true artificial intelligence — “a fully thinking, reasoning, intelligent, autonomous system,” — he would have to start simple. “If I can’t do it at that level, I’m not going to do it at a C-3PO level,” he said. Zeus came first, running on a 9-volt battery and equipped with a basic brain: three neurons on each half, and a communications hub called an artificial prefrontal cortex. Next came Hercules and Athena. And that’s where things really got interesting. Crowder programmed them to avoid light, just like Zeus. But he also designed them to run on solar power. When their batteries ran low, they felt an urge. Hunger. “They have to find light and charge up, only light still hurts them,” Crowder said. “So now they have to balance the instincts of ‘light still hurts, but if I don’t find light, I die.’”

　　EMOTIONS IN MOTION

　　That conflict creates emotion. And emotion is essential to artificial intelligence, Crowder said, because how we feel influences everything we do. “Our entire learning system in our human brain is tied to our emotions,” he said. Emotions help the brain decide how to use its resources — something called cognitive economy, he said. If you’re feeling happy, you’ll respond to an event accordingly. If you’re anxious, or sad, or fearful, your brain might tell you to respond differently. “We need the same thing in AI because no matter how robust you build the system, it has limited memory, limited processors, limited power,” Crowder said. “So I have to understand how to allocate the resources. We do the same thing in our brain. If I have 25 things to worry about and one of them is going to kill me, obviously that one gets the resources.” Emotions such as fear and anxiety can help an artificially intelligent system survive. But other emotions are useful as well. Affection and annoyance, for example. Which brings us to the laboratory of Bill Ferguson.

　　COMPUTERIZED CULTURE

　　How do you get a video game to like you? If it’s the game Ferguson helped build, you bow, point to yourself and say your name. Ferguson, an engineer at Raytheon BBN Technologies in Cambridge, Massachusetts, helped work artificial intelligence into a training tool that teaches Americans how to approach strangers in a foreign land. The videogame-style simulator, built for the Defense Advanced Research Projects Agency, encourages making polite, friendly overtures before taking on tasks such as asking for directions. “People in other cultures want to talk with you for a while. They want to get to know you,” Ferguson said. In one scenario, the user is lost but has a photograph of the destination. Two locals approach, speaking only Esperanto. Using a motion sensor, the system watches and interprets the user’s body language. If the user seems pushy or rude, the characters might back away. If the user shows a little more finesse, the characters might offer a piece of fruit. Once the user has established a little goodwill, the characters will take a look at the photo and point out the way. Behind the on-screen action is some clever programming that controls the characters’ attitude and actions. “When you smile at them, they have an urge to smile back at you,” Ferguson said. “But they won’t smile if they’re irritated.” Other researchers are incorporating similar technology into Raytheon’s Learning Platform. The electronic tutoring system detects when students are having trouble and adjusts its teaching style. Raytheon built the system for the military but is donating it to high schools nationwide for teaching physics and other subjects.

　　BRAINS THROUGHOUT THE BODY

　　Crowder has graduated from the neural system of the cockroach to that of the octopus. Octopuses have a main brain that issues broad commands like “eat” or “move,” then a separate packet of nerves in each arm that knows how to carry out the order. So he built one with an octopus-like neural system. Crowder’s goal is a network of machines that can work together through coordination by a central command unit, one most likely with a person at the helm. Think of a squadron of deep-sea minehunters that can scour the ocean floor on their own and report back to a human controller only when they find something of interest. “They have a sense of their own defense and security, but the operator is the one who’s giving the mission parameters,” Crowder said. “They don’t require a lot of care and feeding.” To Ferguson, who has been working on artificial intelligence systems for more than 30 years, the use of machines to replicate human thought is a clear next step in doing things faster, better and smarter. “A guy with a calculator would have run circles around a guy without a calculator 40 years ago,” he said. “It’s just a new kind of tool that’s helping human intelligence get farther.”（北京航天情报与信息研究所）

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