没有指挥，只有控制
Chaos fills battlefields and disaster zones. Artificial intelligence may be better than the natural sort at coping with it
战场和灾区一片混乱。人工智能应对这种局面的能力可能要胜于人类
Nov 25th 2010 | from PRINT EDITION
2010年11月25日|打印版
ARMIES have always been divided into officers and grunts. The officers give the orders. The grunts carry them out. But what if the grunts took over and tried to decide among themselves on the best course of action? The limits of human psychology, battlefield communications and (cynics might suggest) the brainpower of the average grunt mean this probably would not work in an army of people. It might, though, work in an army of robots.
军队一直都是由军官与士兵所组成。军官发号施令，士兵执行命令。但如果士兵接过了指挥之责，并试图由他们自己商定下一步该干什么，这会出现何种后果？由于人类组成的军队要受到人类心理与战场通信手段的限制，而普通士兵的脑力有限（愤世嫉俗者对此可能要表示反对了），上述原因决定了这样一支军队可能无法遂行其任务。然而，一支由机器人组成的军队却可能以这种方式运作。
Handing battlefield decisions to the collective intelligence of robot soldiers sounds risky, but it is the essence of a research project called ALADDIN. Autonomous Learning Agents for Decentralised Data and Information Networks, to give its full name, is a five-year-old collaboration between BAE Systems, a British defence contractor, the universities of Bristol, Oxford and Southampton, and Imperial College, London. In it, the grunts act as agents, collecting and exchanging information. They then bargain with each other over the best course of action, make a decision and carry it out.
将战场的指挥权交给机器人士兵的集体智慧听起来风险不小，但它正是一个叫做“阿拉丁”的研究项目的核心内容。其全称叫做“分散式数据与信息网络自主学习主体”，按其首字母缩略为ALADDIN（阿拉丁）。这项研究已进行了5年之久，是由英国防务承包商英国宇航系统公司（BAE）与布里斯托大学、牛津大学、南安普敦大学及伦敦大学帝国理工学院合作研发一个项目。在这项研究中，普通士兵担当研究的主体。他们首先收集和交换信息,然后协商讨论最佳的行动方案，做出决定。最后开始行动。
So far, ALADDIN’s researchers have limited themselves to tests that simulate disasters such as earthquakes rather than warfare; saving life, then, rather than taking it. That may make the technology seem less sinister. But disasters are similar to battlefields in their degree of confusion and complexity, and in the consequent unreliability and incompleteness of the information available. What works for disaster relief should therefore also work for conflict. BAE Systems has said that it plans to use some of the results from ALADDIN to improve military logistics, communications and combat-management systems.
到目前为止，“阿拉丁”项目的研究人员只是将他们的试验限制在模拟如发生了地震这类自然灾害上，还没有在模拟战争的情况下进行测试。也就是说试验如何拯救生命，而不是如何夺取生命。从而使这项技术少了几分邪恶的色彩。但自然灾害带来的混乱和复杂局面与战场的情况相差无几，都同样存在难以获得可靠信息与得到的信息支离破碎的问题。用于救灾的有效措施因此也应该适用于战场。英国宇航系统公司表示，它计划将“阿拉丁”项目的部分研究成果应用于改进军队的后勤、通讯和作战管理系统上。
War and peace
战争与和平
ALADDIN’s agents—which might include fire alarms in burning buildings, devices carried by emergency services and drones flying over enemy territory—collect and process data using a range of algorithms that form the core of the project. To develop these algorithms the 60 researchers involved used techniques that include game theory (in which agents have to overcome barriers to collaboration in order to get the best outcome), probabilistic modelling (which is employed to predict missing data and reduce uncertainty) and optimisation techniques (which can provide means of making decisions when communications between agents are limited). A number of the algorithms also employ auctions to allocate resources among competing users.
“阿拉丁”项目的主体可能包括建筑物内的火灾报警器、抢修队携带的设备及飞越敌方领空的无人机等，它们收集信息，并使用构成了研究项目核心的一套算法来处理这些数据。为了开发这套算法，共调用了60名研究人员，使用了包括博弈论（应用这种理论，要求各主体必须消除隔阂，密切合作，以获得最佳的结果）、概率模型（利用这种模型得到的结果来代替无法收集到的数据，减少不确定性）及优化技术（利用这种技术，可以在各主体间通讯联系不畅时提供作出决定的方法）等手段。算法中还大量采用了竞拍的方式在竞争用户间分配资源。
In the case of an earthquake, for instance, the agents bid among themselves to allocate ambulances. This may seem callous, but the bids are based on data about how ill the casualties are at different places. In essence, what is going on is a sophisticated form of triage designed to make best use of the ambulances available. No human egos get in the way. Instead, the groups operating the ambulances loan them to each other on the basis of the bids. The result does seem to be a better allocation of resources than people would make by themselves. In simulations run without the auction, some of the ambulances were left standing idle.
例如在一场地震灾难中，就可以采用各主体竞价的方式来分配救护车。这似乎有些冷酷无情，但出价依据的是各地伤亡严重程度的数据。其实，这一切只是治疗类选法（triage）的一种复杂形式而已，使可调用的救护车得到最佳的利用。人类的利己主义在此就不会来挡道了。分配给各抢救小组的救护车数量完全根据竞标的结果来定。其结果似乎确实比人类自己调配时将资源分配的更合理了一些。在未实施竞标方式的模拟实验中，有些救护车被闲置一旁。
The bidding algorithms can be tweaked to account for changing behaviour and circumstance. Proportional bidding, for instance, allows resources to be shared. If one agent bids twice as much as another for the use of a piece of equipment, the first agent will be given two-thirds of its capability and the second one-third. And, a bit like eBay, deadlines placed on making bids speed the process up.
竞标算法还可以根据作用方式及条件的变化而改进。例如，比例竞标就可以实现资源共享。如为获得某台设备的使用权，一个主体出价是另一个主体的两倍，则第一个主体将获得这台设备全部能力2/3的使用权，而第二个主体只获得1/3。这有点类似于易趣网设置截止时刻以加速竞标进度的做法。
All of which is very life-affirming when ambulances are being sent to help earthquake victims. The real prize, though, is processing battlefield information. Some 7,000 unmanned aerial vehicles, from small hand-launched devices to big robotic aircraft fitted with laser-guided bombs, are now deployed in Iraq and Afghanistan. Their combined video output this year will be so great that it would take one person four decades to watch it. Next year things will be worse. America is about to deploy drones equipped with a surveillance system called Gorgon Stare. This stitches together images from lots of cameras to provide live video of an area as big as a town. Users will be able to zoom in for a closer look at whatever takes their interest: a particular house, say, or a car.
当地震发生，急需救护车前往救助伤员时，上述做法充份显示了其救死扶伤的效果。然而其真正的价值体现在处理战场信息上。目前约有7000架无人飞行器部署在伊拉克和阿富汗，这些飞行器小到可以徒手投掷，大到装备了激光制导炸弹的大型无人机。这些无人飞行器今年拍摄的视频图像合在一起，一个人就是花上40年的时间也难看完。明年这一情况可能会更加严重。美国打算明年部署一种无人机，这型无人机上安装了被称为“戈尔贡凝视”（Gorgon Stare）的一种监视系统。这种系统可以将多台摄影机拍摄的影像进行拼接，合成一幅全城大小的即时影像。使用这些影像的人不论是对地面上的什么发生兴趣（比如一间特定的房屋或是一辆汽车），都可以将画面拉近仔细观看。
Data are also streaming in from other sources: remote sensors operating as fixed sentries, sensors on ground vehicles and sensors on the equipment that soldiers carry around with them (some have cameras on their helmets). On top of this is all the information from radars, satellites, radios and the monitoring of communications. The result, as an American general has put it, is that the armed forces could soon be “swimming in sensors and drowning in data”.
流入的数据也有其它来源，如作为固定岗哨的遥控探头、装在地面车辆上的探头及单兵装备上的传感器（部分士兵的头盔上装有摄像头）。这些还不算什么，数据最大的来源是雷达、卫星、无线电设备和通讯监控系统。其结果就如一位美国将军所言，军人们可能很快就要“在传感器的大海中游泳，淹死在数据的汪洋之中。”
ALADDIN, and systems like it, should help them keep afloat by automating some of the data analysis and the management of robots. Among BAE Systems’ plans, for example, is the co-operative control of drones, which would allow a pilot in a jet to fly with a squadron of the robot aircraft on surveillance or combat missions.
“阿拉丁”及其类似的系统可以使部分数据分析及机器人管理工作实现自动化，因而可以成为军人们的“救生圈”。例如，英国宇航系统公司计划开发的项目之一是无人机的联合控制，这项研究一旦成功，一名喷气机驾驶员就能独自驾机带着一队无人机去分别执行侦查及战斗任务。
The university researchers, meanwhile, are continuing to look at civilian applications. The next step, according to Nick Jennings of the University of Southampton, who is one of the project’s leaders, is to examine more closely the interaction between people and agents. The recent earthquake in Haiti, he says, showed there is a lot of valuable information about things such as water, power supplies and blocked roads that can be gathered by “crowdsourcing” data using software agents monitoring social-networking websites. The group will also look at applying their algorithms to electricity grids, to make them work better with environmentally friendly but unreliable sources of power.
与此同时，各大学的研究者们还在继续探寻这一技术在民用领域的应用前景。尼克•詹宁斯（Nick Jennings）来自南安普顿大学，是该项目带头人之一。按照他的说法，下一步工作是更仔细地检验人与各主体之间的互动情况。他说，最近发生在海地的地震救灾过程显示，大量有价值的信息，如有关供水、供电及道路堵塞等信息可以通过“众包”数据的方式进行收集，这种方式依靠各软件主体密切监视社交网站的动态。这个项目的研究人员还打算将他们开发的算法应用到电网管理上，目的是改进稳定性欠佳的环保型电源入网后电网的运行状态。
And for those worried about machines taking over, more research will be carried out into what Dr Jennings calls flexible autonomy. This involves limiting the agents’ new-found freedom by handing some decisions back to people. In a military setting this could mean passing pictures recognised as a convoy of moving vehicles to a person for confirmation before, say, calling down an airstrike.
为打消人们担心机器会完全取代人类的顾虑，更多的研究成果将带有詹宁斯博士称之为“柔性自主”的特点。通过将部分决定权重归人类的办法来限制各主体自行扩大自由行事权。应用在军事中，这意味着如发现一个移动的车队后，无人机在决定是否对其进行打击前，必须先将图片传给一个人加以确认。
Whether that is a good idea is at least open to question. Given the propensity for human error in such circumstances, mechanised grunts might make such calls better than flesh-and-blood officers. The day of the people’s—or, rather, the robots’—army, then, may soon be at hand.
这样做是否妥当至少还有待商榷。但鉴于人类以往在这类情况下常犯错误，与血肉之躯的军官们相比机器人大兵也许更适于指挥这样的行动。一支人民军队（呵呵，还不如说是机器人部队）的出现可能是指日可待了
博文
没有评论:
发表评论