ARTIFICIAL AL “APPLICATION OF ARTIFICI INTELLIGENCE IN MILIT MI LITARY” ARY”
ARTIFICIAL INTELLIGENCE: INTRODUCTIION:
It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable. Major AI applications define the field as "the study and design of agents,” where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success. Artificial intelligence has been the subject of breathtaking optimism, has suffered stunning setbacks and, today, has become an essential part of the technology industry, providing the heavy lifting for many of the most difficult problems in computer science. HISTORY OF AI:
Evidence of Artificial Intelligence folklore can be traced back to ancient Egypt, but with the development of the electronic computer in 1941, the technology finally became available to create machine intelligence. The term artificial intelligence was first coined in 1956, at the Dartmouth conference, and since then Artificial Intelligence has expanded because of the theories and principles developed by its dedicated researchers. Through its short modern history, advancement in the fields of AI have been slower than first estimated, progress continues to be made. From its birth 4 decades ago, there have been a variety of AI programs, and they have impacted other technological advancements.
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APPLICATIONS OF AI:
Artificial intelligence has been used in a wide range of fields including medical diagnosis, stock trading, robot control, law, scientific discovery and toys. However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labeled AI anymore." "Many thousands of AI applications are deeply embedded in the infrastructure of every industry.” In the late 90s and early 21st century, AI technology became widely used as elements of larger systems, but the field is rarely credited for these successes.
Computer science Military Finance Medicine Heavy industry Transportation Telecommunications Toys and games Music Aviation
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ARTIFICIAL INTELLIGENCE IN MILITARY
AI and the military are slowly getting more and more closely involved, and the military sees the mass potential in Artificial Intelligence on the battlefield. People are precious...silicon isn't. When decisions have to be made quickly (sometimes instantly) taking into account an enormous amount of information, and when lives are at stake, artificial intelligence can provide crucial assistance. From developing intricate flight plans to implementing complex supply systems or creating training simulation exercises, AI is a natural partner in the modern military. The applications of AI in the military are wide and varied, yet due to the robustness, reliability, and durability required for most military programs and hardware. As techniques are refined and improved, more and more AI applications will filter into the war scene - after all, silicon is heap Usage of AI in military according to different authors ANALYSIS
In the first article we read that AI application in war can be traced from 2 nd world war. Autonomous weapons are a revolution in warfare in that they will be the first machines given the responsibility for killing human beings without human direction or supervision. These weapons are first used on machines then on humans. In the second article we have read the implementation of AI in different applications which can be mentioned as: military and aerospace electronics military and aerospace electronics in which the role of defense advanced research projects agency (darpa) of united states was also mentioned and what are the different steps they are taking in this field. The other applications mentioned in the articles are like this Ai Military Aircraft, Radar -Apache Longbow, Autopilot Featured Planes. In addition the applications in NASA, air force and navy were also mentioned. In another article we have found out that; The increasing deployment of gun-toting robots by the U.S. military and other armed forces around the world could end up endangering civilian lives and giving terrorists new ideas, warns a U.K. robotics professor. The U.S. Department of Defense (DOD) has outlined plans to ramp up the use of remotely controlled robotic vehicles on land, undersea and in the air. The goal is to field increasingly autonomous robots — without without a human controller — to dispose of — to explosives, stand guard and spot targets to attack. Nations such as South Korea and the Republic of South Africa have also begun adopting armed robotic systems. Which shows another perspective that although AI is helping a lot in this field but it is a serious threat for the humans? we have also analyzed an article in which the two major challenges for the AI implementation in the future is given the first challenge is about construction of an anticipatory system and the other was to build cognitive models. The future work was also mentioned in the articles that what will be do ne in the future. As with many other fields of scientific study, the military has picked up on the use of Artificial Intelligence. The possibilities of military use of AI are boundless, exciting, intimidating, and frightening. While today's military robots are used mainly to find roadside bombs, search caves, and act as armed sentries, they have the potential to do so much more. In an article we have also read that the military is also trying to create 3
automated vehicles — the ultimate autopilot. Machines already have the ability to see the world around them and read a map, theoretically well enough to be able to drive from point to point without human assistance. However, when the Pentagon first sponsored a competition for prototype-automated vehicles in the Mojave Desert in 2004 to test their resilience against difficult terrain, none of the fifteen entries crossed the finish line. The following year, a car built by students at Stanford University completed the 131 mile course in six hours and 53 minutes. The car completed the race without any human input, using only onboard computers and sensors to navigate terrain meant to mimic combat conditions in Iraq and Afghanistan. Though this proved that great strides had been made in one year alone, even more are needed before the technology can be marketed and put to real use. According to the Pentagon, actual robotic soldiers powered by Artificial Intelligence will be a major fighting force in the American army, probably within the next decade. The first robot soldiers will actually be remote-controlled vehicles. The military has poured tens of billions of dollars into this project already. Congress wants to see this happen, and they ordered that a third of all military vehicles and deep-strike aircraft be automated by 2010.As the machines begin to think, see, and react more like humans, the level of their autonomy and our level of trust in them will grow as well. However, it is predicted that a true soldier-simulating robot will not come about for another 30 years. These robots need to be able to determine friend from foe and enemy from bystander, and teaching them to do so will require a tremendous amount of research and work. The government has assured us however that these robotic soldiers will not be put into the field and allowed to make such decisions until they are read y to do so. Another current infantry prototype knows how to recognize an enemy when it is under fire. When this happens, it can react to enemy fire on its own or follow orders given to it from a remote observer. Although it's programmed to work autonomously, in its present state, it still requires some set of outside monitoring controls in order for it to work. Its designers plan to have it usable for infantry missions by 2015 . Another one of their prototypes nearly realizes the anthropomorphic goal imagined by Isaac Asimov in his I, Robot book. This prototype is a machine about four feet high with a Cyclops eye and a gun for a right arm. It is programmed to perform basic hunting and killing tasks. It can actually find valid targets on its own and can shoot at them with remarkable accuracy. The list of benefits of using machines to achieve military goals is long and significant. The immediate and most evident boon of such technology is the elimination of human risk: machines, not humans, would be lost in battle. In addition, specialized robots can be designed to accomplish specific tasks more effectively than humans can, increasing the military's overall effectiveness. They are also more cost-effective. Robots will always be able to do what they were designed to do and can be recycled when they are obsolete. A human soldier costs on average $4 million dollars over his lifetime, and the U.S. Pentagon cannot obtain the money to pay all of them. Robots could cost a tenth of that amount or less. Although the ultimate goal of the robot soldier is to completely eliminate human risk, even the experts say that war will always be a human endeavor involving human loss of life, no matter how much the AI warrior is developed. New ethical 4
questions will arise once we have the ability to invade countries without risk of bloodshed on the part of the invader. And even though these robotic developments will soon be on our doorstep, it’s a little frightening to see that the only ones who are addressing the issue of use and or misuse of such technology are the scientists and the authors of science-fiction. MILITARY:
The military and the science of computers has always been incredibly closely tied - in fact, the early development of computing was virtually exclusively limited to military purposes. The very first operational use of a computer was the gun director used in the Second World War to aid ground gunners to predict the path of a plane given its radar data. Famous names in AI, such as Alan Turing, were scientists that were heavily involved in the military. Turing, recognized as one of founders of both contemporary computer science and artificial intelligence, was the scientist who broke the German's Enigma code through the use of computers. As computing power increased and pragmatic programming languages were developed, more complicated algorithms and simulations could be realized. Computers were soon utilized to simulate nuclear escalations and wars or how arms races would be affected by various parameters. The simulations grew powerful enough that the results of many of these 'war games' became classified material, and the 'holes' that were exposed were integrated into national policies. MORALITY: A QUICK THOUGHT
All the systems in military are quite impressive, and perfected models could prove incredible assets on the battlefield. Artificial Intelligence may only get developed to a certain level due to the threat humans feel as computers get more and more intelligent. The concept behind movies such as Terminator where our robotic military technology backfires on us and destroys us are rampant Autonomous weapons are a revolution in warfare in that they will be the first machines given the responsibility for killing human beings without human direction or supervision. To make this more accurate, these weapons will be the first killing machines that are actually predatory, that are designed to hunt human beings and destroy them. APPLICATION IN THE MILITARY: 1. MILITARY AND AEROSPACE ELECTRONICS:
After decades of research and disappointing results, military experts start to see new directions for artificial intelligence in data processing, pattern recognition, and decision aids. In Navy AI addresses the automation and extension of human intellectual skills specifically human decision making and autonomous devices. Both have their civil and military counterparts. In the former category, decision making, the military employs AI
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for planning and logistics functions. In the commercial world similar techniques help business leaders streamline retailing and financial operations by extracting relevant data. DEFENSE ADVANCED RESEARCH PROJECTS AGENCY (DARPA) OF UNITED STATES:
Autonomous devices were well established in manufacturing industries before U.S. military experts launched their theoretical studies under the Strategic Computing Program at the Defense Advanced Research Projects Agency (DARPA) in the 1980s.With a combination of military-funded development programs and the availability of commercial off-the-shelf (COTS) technology, the military services are beginning to implement AI methods in such new generations of weapons platforms as unmanned aerial vehicles (UAVs) and autonomous submersibles to perform unmanned surveillance in shallow waters. Much touted in the past in such programs as DARPA's Pilot's Associate, modern expert systems are evolving in two directions:
rule-based reasoning case-based reasoning
RULE-BASED REASONING:
The traditional rule-based systems, which were supposed to capture the best expertise of pilots and other skilled personnel, tend to be more detailed and smaller in their scope of information. Military service leaders face a comparable problem of sorting out how much robotics they want. The long-term challenge is to evolve toward automation in battle "with confidence." CASE-BASED REASONING:
Case-based reasoning which is the way humans learn, involves storing previous problems and solutions and then identifying a match when a new situation arises. Meyrowitz calls this approach "more abstract and higher level," as case-based expert systems extract rules from cases over time. Some computer scientists argue that this capability represents the beginning of "machine learning." Critical to the ability to employ this method is the availability of large, affordable computer memory and this is where AI is riding the crest of today's commercial electronics technology. DARPA’S WORK IN DIFFERENT FIELDS:
DARPA continues military AI air-traffic project:
DARPA, the US warboffin bureau which curls a supercilious lip at established wisdom and tweaks the nose of consensus opinion, has decided to press ahead with its automated artificial-intelligence air traffic control system. The move is doubly welcome here at 6
Vulture Central: not only is it a tasty tech-news nugget, but the lack of any ultra puissant automated air-traffic systems is one of the factors delaying our long-awaited flying cars. DARPA has approved the move forward to phase two of GILA, the Generalized Integrated Learning Architecture. GILA, under development by US wartech behemoth Lockheed and academic partners, is intended initially as a planning and training aid for US military air-traffic controllers. In time, it is hoped that the system will be able to learn from its human colleagues and eventually surpass them. The company believes that GILA will become a true expert system, able to build up knowledge in a continual process - unlike human traffic controllers, who inevitably leave the service or retire. DARPA hope that GILA will allow deployed US forces to manage crowded airspace above future battlefields and war zones more efficiently, allowing manned and unmanned aircraft, drones, weapons and so forth to cooperate without the crippling planning and authorization delays .This sort of automated routing and planning system , with fasterupdating and more accurate air tracking - might one day permit much larger numbers of aircraft to operate safely in a given volume of civil airspace. People would still never be able to fly it in any numbers numb ers because this would overload the air-traffic system. On another note, it seems almost superfluous to point out that military AI software controlling fleets of murderous aerial war robots could easily have been more appropriately named. "Skynet" leaps to mind, for instance.
DARPA targets ultimate artificial intelligence wizard
The military's expert research and development arm isn't always about making bigger, better things that blow up or fly fast, sometimes it wants to develop monster brain power. In this case it wants to build avant-garde artificial intelligence (AI) software known as a Machine Reading Program (MRP) that can capture knowledge from naturally occurring text and transform it into the formal representations used by systems. The idea is that such an intelligent learning system would unleash a wide variety of new AI applications military and civilian ranging from intelligent bots to personal tutors according to DARPA. EXAMPLE:
All of the text in the World Wide Web will become available for automating the monitoring and analysis of technological and political activities of nations; plans, rhetoric, and activities of transnational organizations; and scientific discovery within various disciplines, DARPA stated. New avenues of cultural awareness and historical research will be enabled. With truly general techniques for effectively handling the incompatibilities between natural language and the language of formal inference, a system could be constructed that maps between natural and formal languages in any subject domain.
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DARPA said that nearly all successful AI systems today succeed because they possess sufficient consistent, relevant knowledge about a given problem. However, since large amounts of knowledge are almost always needed for this success, AI systems require this knowledge to be expressed in a logical formula of some type. Manually encoding such knowledge can become prohibitively expensive. The most flexible and ubiquitous medium used to capture knowledge about the diverse areas of human interest, it is natural to consider making it feasible for AI reasoning systems to employ this vast store of human knowledge. As AI systems currently cannot use such knowledge, it would be revolutionary if technology could be developed to bridge this gap, DARPA said. The military frequently faces impediments to stability and reconstruction operations in a new location due to the lack of understanding of the local situation. Similarly, strategic assessment of a foreign nation's science and technology base involves the continuous assessment of technical articles. This information is often available on the Web, and some tools to assist this analysis are available, but the process would be significantly enhanced by a system that could directly analyze the information found in these text sources. DARPA lists some the technological goals of the new AI system as follows:
A Universal Reading System: Create a universal Reading System that can take any natural text and any reasoning context as input and can effectively apply the knowledge contained in that text in that reasoning context Enhanced Capabilities from Combining natural language and AI reasoning NLP and AI reasoning into new technology that provides the benefits of both Domain-Specific Performance from a General-Purpose System: Develop a general-purpose text-reading "front-end" (Reading System, for short) that can be used with any number of domain-specific reasoning systems (DSRS). Couple NLP and Convergent Knowledge: The goal in coupling NLP with convergent knowledge - knowledge that is mutually constraining - is not to understand facts implied by a single sentence in isolation. Rather, the goal is to uncover physically remote facts, contexts and determine how these bits of knowledge can, in turn, help make the NLP feasible by constraining the interpretation of other such bits of information. Deployment of NLP in a Wide Range of Practical Reasoning Contexts: Develop easily reused and re-purposed NLP technology that can be rapidly applied in a wide range of practical reasoning contexts where textual knowledge could provide strong value. Research Community in Machine Reading: Another Anoth er important goal is to nurture a research community that focuses on the machine reading problem.
DARPA has been interested in exploiting the promise of AI for years. The Generalized Integrated Learning Architecture (GILA) system, developed by Lockheed Martin's Advanced Technology Laboratories under a $22 million, 48-month contract, is intended to help the Air Force in particular keep airspace operating safely with increased air traffic and the advent
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2. AI MILITARY AIRCRAFT:
AI General Aviation and AI Military aircraft seem to have been given a low priority by developers in the past, and as real world pilots and ATCs, we have decided to create as many of the most popular General Aviation and Military aircraft for AI use. It provides good experience of more realistic environment on flight simulator when flying into or out of general aviation or military airfields. Populate your general aviation and military airfields with types of aircraft that you would expect to find at these airfields. Our AI aircraft are based on the types of aircraft which are generally seen operating from these airfields. We believe that we have achieved an excellent compromise between aircraft detail and frame-rate. These aircraft were designed using FSDS Version 2.24 and have the necessary moving parts for AI. All aircraft are grouped together in volumes. This Volume is based on aircraft of the South African Air Force, past and present. There are six AI aircraft in this volume and there is no restriction on re-paints. Please feel free to modify the textures to suit yourself. We will be producing most of the popular makes of General Aviation and Military aircraft.
RADAR -APACHE LONGBOW:
AI can be used to protect the safety of the crew. For example, the radar of the Apache Longbow uses advanced algorithms that can accurately determine whether the threat detected is in fact a threat. This is important, since in the heat of battle it is hard to distinguish radar returns manually, accurately and quickly. An error could be fatal which could blow up the palm tree, but get shot down by the T-80 tank 25 meters to the right of it.
AH-64D Apache Longbow
AUTOPILOT FEATURED PLANES:
One of the most important usage of AI are the advanced autopilot features, that take away the tedious tasks of flying, so that pilots can focus on the important tasks. Automated landing systems, or Computer-aided landing systems can greatly decrease peacetime and wartime accidents when landing on carriers (especially at night). The main military value of such projects is to reduce the workload on a pilot. Modern pilots work in incredibly complex electronic environments - receiving information not only from their own radar, but from many others (principle behind J-STARS). Not only is the information load high, the multi-role aircraft of the 21st century have highly complex avionics, navigation, communications and weapon systems. All this must be organized in a highly accessible way. Through voice-recognition, systems could be checked, modified and altered without the pilot looking down into the cockpit. Expert/advisory systems 9
could predict what the pilot would want in a given scenario and decrease the complexity of a given task automatically. Aside from research in this area, various paradigms in AI have been successfully applied in the military field. For example, using an evolutionary algorithm (EA) to evolve algorithms to detect targets given radar/FLIR data, or neural networks differentiating between mines and rocks given sonar data in a submarine. 3. AUTOMATED SYSTEM:
SCHEDULING
AND
PLANNING
ENVIRONMENT
JPL experts are implementing what is known as the Automated Scheduling and Planning Environment system, or ASPEN, as a sort of command and control architecture in which participating scientists can do data mining to achieve sensor fusion. It in effect gets all the participants on the same page so they can tell NASA what data products they want. The spacecraft knows the constraint parameters and automatically generates the data according to plan. Experts credit ASPEN with reducing the acquisition planning time from a three-year process to one week for an Antarctic mapping mission conducted in September every year. Furthermore, ASPEN is to be used in an Explorer spacecraft mission conducted by the University of Colorado and scheduled for launch later this month. EXAMPLES OF JPL:
An example is what JPL officials call their operations mission planner for its 26-meter antenna sub network. They have used AI since 1993 and have reduced the scheduling effort by 30 percent while doubling network support, according to Chien. Another is an automated image processor for synthetic aperture radar data, which has cut manual inputs by a factor of 10 and reduced the amount of central processor time necessary for processing by 30 percent. Also at JPL a program known as Continuous Activity Scheduling, Planning, Execution and replanning, or CASPER, is the real-time version of ASPEN that does planning and execution, and is designed for flight use as part of the flight software. CASPER is for another University of Colorado mission scheduled for launch in the summer of 2002.
SRA DEVELOPES NASDAQ:
A system that SRA experts developed for NASDAQ four years ago detected new patterns of fraud by perpetrators who, like enemy missiles, "fly below the radar." Without data mapping these incursions would go undetected, Blejer maintains. "There are not enough human eyes." The company has also worked on physical intrusion-detection systems for the military. military. These new data-mapping systems are hardware- and software-independent, software-independent, she says: "NT, Unix, Linux, whatever." All the hardware and software are readily 10
available off the shelf. The trick is to integrate all the components and thus add value in business-to-business as well as military applications.
NAVY EVALUATES SHIPBOARD NETWORK TO COORDINATE:
A form of artificial intelligence is coordinating scheduling information aboard the guided missile destroyer USS McFaul (DDG 74) to coordinate scheduling information on the Norfolk, Va.-based Arleigh Burke-class warship. A data synchronization software package known as ScoutWare from Aether Systems Inc. of Owens Mills, Md., ties together Palm hand-held terminals from Palm Inc. in Santa Clara, Calif., with a server from Clarinet Systems in San Jose, Calif. The ship's crewmembers use the system to send and receive e-mail, conduct training and evaluations, consolidate checklists and databases, and coordinate schedules. The wireless system is initially limited to about 150 officers and sailors using the Palm devices on the destroyer, and the purpose is to improve response times to boost combat readiness. By coordinating sensor data into a shared network, the crewmembers should have a better picture of the operations under way. The McFaul is one of the ships able to launch Tomahawk cruise missiles, and it also performs anti-submarine warfare missions. All the hardware is commercial off-the-shelf, and the Navy is using the McFaul as the test ship for possible application of the software package throughout the Atlantic Fleet. The U.S. Army has also been considering this technology for use with its medical research databases, and the Air Force is looking into it for inspections of aircraft on the flight line.
AI TECHNIQUES AT AIR FORCE RESEARCH LAB TO EXTEND TARGET IDENTIFICATION:
One of the ways artificial intelligence can extend military capabilities is in interpreting "non-literal sensors," the chief of the target recognition branch in the Sensors Directorate of the Air force Research Laboratory at Wright-Patterson Air Force Base in Dayton, Ohio. The medical community uses similar AI techniques for X-ray interpretation, and the military can put this technology to work for its unique missions, such as distinguishing a tank from a school bus. Nelson(the chief), who quips that AI is "what you haven't done yet," is investigating control programs based on what are known as genetic algorithms to enable aircraft to get smarter after each battle. Like the human genes for which they are named, genetic algorithms permit knowledge to be passed down from one generation of weapon system to another. The effort also involves data mining.The Air Force, like companies, has vast databases and we need to get useful patterns. The approach is to organize the data into a table in which each column is a different attribute of the target and each row is the target.
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By using AI techniques to reduce the number of columns, the idea is to find the minimum number of features to identify all targets. He estimates this data reduction can cut the 128 candidate attributes to about 25 important attributes for target recognition.
4. ARMY SCIENTIST: COMPUTER POWER-ANSWER TO ALL AI NEEDS:
Computing power is the answer to applying artificial intelligence techniques to the military's needs. Instead, specialists need a combination of AI techniques, such as neural nets and expert systems, says Gerald Powell, deputy director for the operations directorate at the Software Engineering Center of the Army's Communications and Electronics Command (CECOM) at Fort Monmouth The need for a combination of computational technologies is especially true for the Army's logistics planning to support the ammunition and petroleum needs of deployed forces and this technology can be shared with the commercial sector. Despite the big AI push among the services and the Defense Advanced Research Projects Agency in the 1970s and '80s, slowdown in the rate of research in the commercial sector which takes the lead and the military attempts to focus on its unique requirements. The solution he envisions is integrating such technologies as neural networks and genetic algorithms to tackle pressing problems like automatic target recognition. As an example of why raw computing power is not the whole solution, he cites a 1956 study by Dartmouth University that found in the game of chess there were 10 to the 120th power possible moves. This is far beyond the capability of any human or even any conceivable supercomputer that could be developed. To illustrate that level of complexity, physicists estimate that the total number of subatomic particles in the universe is about 10 to the 85th power. To put it even more dramatically, if there were 10 to the 86th power of elementary particles, there would be nine more universes just like this one. 5. NASA ROBOT IN FORM OF SNAKE PLANNED TO PENETRATE INACCESSIBLE AREAS: NASA engineers are developing a new type of snake-shaped robot at the NASA Ames Research Center in Mountain View, to explore e xplore areas where a wheeled robotic rob otic rover might get stuck or topple over. Engineers have built a mechanical prototype of what NASA leaders are calling the "snakebot", lead engineer on the project. The NASA team is now working on the sensors and microcontrollers for operational use. Team members also plan to write software to enable the device to learn by experience in crawling over various surfaces and climbing over obstacles. The NASA center is working with the nearby Xerox Palo Alto Research Center in Palo Alto, where the developer has developed a slightly different version
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known as the "polybot." The next step is to simulate the snakebot in a computer program to develop control procedures. The purpose is not to replace NASA's existing wheeled robots, such as those used to explore the surface of Mars, but to complement them with a smaller, cheaper device that can operate independently in tight places. One of the advantages is the robot's ability to crawl off a spacecraft lander without a ramp. 6. THE ARMY'S ARTIFICIAL INTELLIGENCE INVADES WOW:
Invasion of Army Artificial Intelligences masquerading as real players in World of Warcraft is to test the AI's ability to be a "fake" human by letting it interact with real humans in a virtual world. This isn't the first time military used WoW for training purposes, which is the nominal purpose of the new AI research.
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HOW MILITARY ROBOTS WORK:
The U.S. military has been developing robotic systems e.g. the bulldozer-size ACER can handle tasks like clearing explosives and hauling cargo.
FLYING BOTS: PREDATOR
Predators plays a key role in military planning drones help military commanders keep track of their own troops and also spot enemy troops that might be waiting to ambush U.S. soldiers.
Flying robots like the Predator provide constant real-time data on troop movements, enemy locations and weather. A flying robot did a lot more than just spot the enemy: Predators can be fitted with Hellfire missiles, and when one of these Air Force drones spotted an anti-aircraft gun in southern Iraq in March 2003, it used one of the Hellfires to take it out
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Today's military robots are limited in their autonomy and their range. They are essentially tethered to human controllers. DARPA, the U.S. government entity that funds and develops new technologies for military use, recently held a widely publicized robot race to see how far along robot AI had come. It turns out that AI is still pretty limited not a single robot completed the course. So even as the abilities of robots increase, it seems that for the foreseeable future, a human soldier will still be required at the control unit.
SMALL BOTS: TALON
The most common robots currently in use by the military are small, flat robots mounted on miniature tank treads. These robots are tough, able to tackle almost any terrain and usually have a variety of sensors built in, including audio and video surveillance and chemical detection. These robots are versatile, with different sensor or weapon packages available that mount to the main chassis. Virtually all of them are man-portable. The TALON is a man-portable robot operating on small treads. It weighs less than 100 lbs (45 kg) in its base configuration. Some time later, the soldiers set up the TALON's control unit and simply drove it out of the river which brings up another important feature of the TALON .TALON is operated with a joystick control, has seven speed settings and can use its treads to climb stairs, maneuver through rubble and even take on snow.
TALON configurations
The military is performing additional tests using TALON robots equipped with grenade launchers and anti-tank rocket launchers.
SMALL BOTS: MATILDA
MATILDA (Mesa Associates' Tactical Integrated LightForce Deployment Assembly), made by Mesa Robotics, is similar to other small robot designs but has a higher profile due to its triangular tread shape. It weighs 61 lbs (28 kg) with the batteries, can be carried by one or two people and fits in the trunk of a car. MATILDA has numerous possible configurations. For instance, it can be equipped with a mechanical arm or a variety of cameras and sensors, and it can even tow a small trailer. MATILDA with mechanical arm
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The robot has a top speed of 3 feet (1 meter) per second and a single-charge run time of four to six hours. In the event of tread damage, the quick-change tracks can be swapped in about five minutes. 8.
MILITARY AI WORKS(MAIW) :
Military AI Works, (MAIW) along with World of AI is very excited to present its first
two releases. MAIW, which is dedicated to bringing fine military AI packages have released the Seaboard ANG package and the Osan Airbase package for FS2004.Osan Airbase is a FULL AI package which includes flight plans for: the B-1900D transport aircraft, A-10's, and F-16C/D's. The package includes all needed models/repaints, AFCADS, and Voice packs. The Seaboard ANG is a complete AI package which includes:
AI for 8 Air National Guard A-10, F-16, C-130 and C-40 squadrons in Delaware, Maryland, Virginia, North Carolina and the District of Columbia. It also includes all the needed Voice packs, models/textures, and AFCADS to get this wonderful package in the skies MAIW is also excited to be partnered with the fantastic group World of AI, who have generously allowed to release release the packages with the fantastic fantastic WoAI automatic installer
MILITARY AI FOR FLIGHT FOR FLIGHT SIMULATOR:
Spanish Mirage F1's Ready for Action
This package, from Military AI Works, depicts the Dassault Mirage F1’s currently in service with the Spanish Air Force. Featuring custom made scenery for Albacete Air Base and a custom designed afterburner effect.
McConnell AFB Package
McConnell Air Force Base, home the US Air Force's 22nd Air Refueling Wing, comes to life with our rendetion of this strategic base located in the central United States. Complete with custom scenery including scenery for the nearby Cessna Aircraft Field Airport, the base is alive with activity. This is first package featuring the so called "Super Wings" of KC-135's for the U.S. Air Forceand later on other packages will be launched.
Army Air Corps WAH-64 Apaches
This extensive package covers all current operational WAH-64 Apache units of the Royal Army Air Corps Squadrons . Included in this package is custom scenery that will bring life to the default FS9 locations and several of the firing ranges. 15
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Navy Center for Applied Research in Artificial Intelligence (NCARAI):
The Navy Center for Applied Research in Artificial Intelligence (NCARAI) has been involved in both basic and applied research in artificial intelligence since its inception in 1981. This year we celebrate our 25th anniversary. NCARAI, part of the Information Technology Division within the Naval Research Laboratory, is engaged in research and development efforts designed to address the application of artificial intelligence technology and techniques to critical Navy and national problems. The research program of the Center is directed toward understanding the design and operation of computer systems capable of improved performance based on experience; efficient and effective interaction with other systems and with humans; sensor-based control of autonomous activity; and the integration of varieties of reasoning as necessary to support complex decision-making. The emphasis at NCARAI is the linkage of theory and application in demonstration projects that use a full spectrum of artificial intelligence techniques. The NCARAI includes the Adaptive Systems section, the Immersive Simulations section, the Intelligent Multimodal/Multimedia Systems section, section, the Intelligent Systems section, section, and the the Interface Design and Evaluation section. section. INTELLIGENT SYSTEMS:
The Intelligent Systems Section at the Navy Center For Applied Research in Artificial Intelligence (NCARAI) performs state-of-the-art research in cognitive robotics and human-robot interaction, the cognition of complex visualizations, graph comprehension, interruptions and resumptions, spatial cognition, robotics, audition, and software and hardware for sensing and perception. NCARAI techniques contribute to more intelligent systems that require less human intervention, and allow faster, less-expensive development of autonomous systems and vehicles. The Navy Center for Applied Research in Artificial Intelligence develops software for dynamic autonomy and human interaction using robots such as this one, nicknamed “Magneto.” ARTIFICIAL INTELLIGENCE TECHNOLOGIES:
The Navy Center for Applied Research in Artificial Intelligence (NCARAI) of the Naval Research Laboratory (NRL) is engaged in research and development efforts designed to address the application of artificial intelligence (AI) technologies and techniques to critical Navy and national problems. The emphasis at NCARAI is on the linkage of theory and application in demonstration projects that use the full spectrum of AI methods. Current research and exploratory development is concentrated in the following areas: 16
autonomous systems (evolutionary algorithms, hybrid learning methods, adaptive systems, adjustable autonomy, intelligent control, human-robot interaction, cooperative/collaborative teams, cognitive information processing, computer vision); human-computer interaction (multimodal interfaces, audio perceptual processing, interfaces to virtual environments, natural language understanding, speech recognition and understanding, visualization, information retrieval and presentation); intelligent decision aids (case-based reasoning, planning, knowledge management). Topics in distributed AI may be addressed that are related to either autonomous devices or to intelligent decision aids.
10. AI USES - AI GOES TO WAR:
As with many other fields of scientific study, the military has picked up on the use of Artificial Intelligence. The possibilities of military use of AI are boundless, exciting, intimidating, and frightening. While today's military robots are used mainly to find roadside bombs, search caves, and act as armed sentries, they have the potential to do so much more. Not all military uses of AI directly relate to the battlefield however; it can use Artificial Intelligence for more passive purposes as well. For example, the military has developed a computer game that uses AI to teach new recruits how to speak Arabic. The program requires soldiers to complete game missions during which they must be able to understand and speak the language. This system gives the soldiers a more realistic, easy, and effective way to learn the new tongue. This particular game works by using speech recognition technology that evaluates the soldier's words and detects common errors. It can then create a model of the soldier, keeping track of what he's learned and what he hasn't in order to provide individualized feedback for the soldier's specific problems. Those who are working on this project believe that it will change the face of all language learning and similar programs will become mainstream sometime in the near future. The military is also trying to create automated vehicles — the ultimate autopilot. Machines already have the ability to see the world around them and read a map, theoretically well enough to be able to drive from point to point without human assistance. However, when the Pentagon first sponsored a competition for prototypeautomated vehicles in the Mojave Desert in 2004 to test their resilience against difficult terrain, none of the fifteen entries crossed the finish line. The following year, a car built by students at Stanford University completed the 131 mile course in six hours and 53 minutes. The car completed the race without any human input, using only onboard computers and sensors to navigate terrain meant to mimic combat conditions in Iraq and Afghanistan. Though this proved that great strides had been made in one year alone, even more are needed before the technology can be marketed and put to real use. According to the Pentagon, actual robotic soldiers powered by Artificial Intelligence will be a major fighting force in the American army, probably within the next decade. The 17
first robot soldiers will actually be remote-controlled vehicles. The military has poured tens of billions of dollars into this project already. Congress wants to see this happen, and they ordered that a third of all military vehicles and deep-strike aircraft be automated by 2010. As the machines begin to think, see, and react more like humans, the level of their autonomy and our level of trust in them will grow as well. However, it is predicted that a true soldier-simulating robot will not come about for another 30 years. These robots need to be able to determine friend from foe and enemy from bystander, and teaching them to do so will require a tremendous amount of research and work. The government has assured us however that these robotic soldiers will not be put into the field and allowed to make such decisions until they are ready read y to do so. Another current infantry prototype knows how to recognize an enemy when it is under fire. When this happens, it can react to enemy fire on its own or follow orders given to it from a remote observer. Although it's programmed to work autonomously, in its present state, it still requires some set of outside monitoring controls in order for it to work. Its designers plan to have it usable for infantry missions by 2015 . Another one of their prototypes nearly realizes the anthropomorphic goal imagined by Isaac Asimov in his I, Robot book. This prototype is a machine about four feet high with a Cyclops eye and a gun for a right arm. It is programmed to perform basic hunting and killing tasks. It can actually find valid targets on its own and can shoot at them with remarkable accuracy. The list of benefits of using machines to achieve military goals is long and significant. The immediate and most evident boon of such technology is the elimination of human risk: machines, not humans, would be lost in battle. In addition, specialized robots can be designed to accomplish specific tasks more effectively than humans can, increasing the military's overall effectiveness. They are also more cost-effective. Robots will always be able to do what they were designed to do and can be recycled when they are obsolete. A human soldier costs on average $4 million dollars over his lifetime, and the U.S. Pentagon cannot obtain the money to pay all of them. Robots could cost a tenth of that amount or less. Although the ultimate goal of the robot soldier is to completely eliminate human risk, even the experts say that war will always be a human endeavor involving human loss of life, no matter how much the AI warrior is developed. New ethical questions will arise once we have the ability to invade countries without risk of bloodshed on the part of the invader. And even though these robotic developments will soon be on our doorstep, it’s a little frightening to see that the only ones who are addressing the issue of use and or misuse of such technology are the scientists and the authors of science-fiction.
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11. MILITARY AI COULD RULE THE INTERNET:
In various possible types of AI, the most revolutionary would be an intelligent machine that uses the Internet to train of a militarycommissioned National Research Council report on emerging cognitive neuroscience. With so much information online and constantly updated system that reasoned like a human being could be achieved, there would be no limit to augmenting its capabilities. There is something vaguely creepy about the idea of greater-than-human artificial intelligence unleashed on the Internet by the military. Many efforts, large and small, to reach this goal have not yet succeeded perhaps because natural intelligence is still such a mystery to us. 12. NEW CHALLENGES FOR AI IN MILITARY SIMULATION: ARE MULTILEVEL HETEROGENEOUS MODELS THE SOLUTION?
As our nations military forces face new challenges in the field as the result of trying to defeat unconventional adversaries, so it goes with our military modeling and simulation (M&S) community, who are attempting to build decision support tools for our command staff. This paper will address two extraordinarily large issues which the M&S community seeks to make progress on, and how multilevel heterogeneous models (MHM) may play a major part in moving forward. The first of the issues concerns modeling our adversaries, who we conceive of as being an organization: from nation-states to terror cells, as systems with interdependent political, military, economic, social, infrastructural, and information-based components. Secondly, we face the more daunting problem of developing cognitive models of the human elements within these systems: from leaders of countries to the common citizen and everything in between. However, there seem to be parallels between these problems in that they both are readily able to be modeled by as multilevel heterogeneous systems. In this paper, I argue that while both problems are able to be modeled as MHMs, the real issue lies in providing strategies for integrating among the parts of the MHMs. TWO MAJOR CHALLENGES: CONSTRUCTION OF AN ANTICIPATORY SYSTEM:
As a community, we face two major challenges: the first challenge concerns the construction of an anticipatory system which will capture the nonlinear relationships between the different elements in the battle space. We dub this the battle space characterization problem (BCP). Particularly, we are interested in the interplay between political, military, economic, social, infrastructure, and information-oriented elements 19
involved in the conflict. These can vary from the relationship between the condition of national infrastructure and the number of revolutionary movements within the country, to the relationship between social structures (such as the religious affiliation of a clan) to the local economy. This latter relationship may instantiate as a local cleric (of said religious affiliation) demanding a workers strike among his congregation as a result of a government policy which he feels is unfair. TO BUILD COGNITIVE MODELS:
The second of our major challenges is to build cognitive models of the human elements of the battle space. Again, this is a remarkably lofty goal: one which has been elusive since the inception of both AI and cognitive science as academic fields. I am not under the impression that any of us in the military M&S community are expecting a solution any time in the near future, but we are hoping at the minimum to isolate and analyze some of the more difficult aspects of the problem in light of hardware, software, and theoretical advances. The problem of developing computational cognitive models capable of achieving humanlevel intelligence (at least in a somewhat rich domain) is the perfect opportunity for a renewed dialogue between AI researchers and cognitive scientists. I propose that multilevel heterogeneous models can be utilized in making progress on both of these daunting challenges, particularly in the development of cognitive models cognitive models of multi-agent systems (CMMAS) which will be used to implement both single and multi-agent systems of human actors with an eye to fidelity of behavior. I view each challenge as an instance of an integration problem between system elements (either battle space elements or specifically human elements) at a number of levels of abstraction (multilevel) and over a number of different representations (heterogeneity). The multilevel integration problem is endemic to the multi-agent systems community, often dubbed the “micro-macro” problem, and bidirectionally relates the behavior of atomic elements (individual agents) with aggregate elements (such as organizations, groups, cultures, societies, et cetera). In the battle space characterization problem, the multilevel problem appears not only in differentiating individual human elements from groups, but also in relating the behavior of gubernatorial powers from the village-level to the national-level, or regional microeconomics to national macroeconomics among others. The heterogeneity problem arises in both challenges ch allenges as well. In the case of the BCP, information regarding the political, military, economic, social, infrastructure, and informational (PMESII for short) aspects of the battle space cannot usually be captured using a homogeneous computational representation (numbers or symbols) or dealt with in a methodologically pure way (a completely logic-based, or Bayesian solution, for example). Usually, each modeler develops his/her characterization of some aspect of the battle space in a formalism of choice. How do we get all of these models, operating over multiple representations and using multiple computational methodologies to talk to one another? The heterogeneity problem also expresses itself at the level of developing CMMAS. Even at the level of developing computational cognitive models of single agents, the heterogeneity problem arises. For example, one of 20
the dominant themes in Ron Suns CLARION architecture (Sun 2001) involves capturing the distinction between implicit and explicit learning processes. Implicit knowledge is usually characterized as distributed, not consciously accessible, and therefore unable to be verbalized; whereas explicit knowledge is has a localist representation, is consciously accessible, and therefore able to be verbalized. How do implicit and explicit learning processes interact with one another? This is a classic case of heterogeneity in the human cognitive architecture. Both CMMAS and the BCP are facing the same conundrum: they are both naturally modeled as multilevel heterogeneous systems, yet both face a serious problem of integration. 13. FUTURE WORK: COMBAT SYSTEMS:
The Future Combat Systems (FCS) initiative is a massive overhaul of military technology intended to prepare the U.S. Army for modern warfare. Current projections suggest that it will be the most expensive military project in U.S. history and will take decades to design and complete. Creating the hardware, software, networks and integration necessary to make FCS work is an incredibly complicated project. The Army wants to dominate the full-spectrum battlefield - land, sea and air. To accomplish this, it will need several different types of units. The Army must also link its operations with that of the other military branches, and the militaries of other nations that might join them in a coalition operation. An Army poster designed to promote the Future Combat Systems.
FCS is a "system of systems," because it actually comprises 18 separate systems. Each system is a type of unit, such as an unmanned artillery vehicle, a manned tank or a command and control vehicle. FCS is also sometimes called "18+1+1," where the "+1"s represent the network and the soldier who will utilize the systems. If the Army were simply revamping their military hardware and designing 18 new combat and logistics units, that would be a major project by itself. Designing all 18 from the ground up with the architecture to link every unit makes FCS truly revolutionary. So why is the Army undertaking such a huge project? Military experts believe the nature of warfare is changing. Large-scale territory battles like those fought in World War II will disappear. Instead, the Army will probably face insurgencies and smaller conflicts 21
spread out over wide areas. Tomorrow's Army needs the ability to deploy and redeploy as quickly as possible. To this end, the FCS has four main goals:
Improve strategic agility
An Army with large, inflexible units that take months to deploy can't react quickly enough or deal with all of the problems at hand. Some military analysts refer to this as "having a pocket full of $20 $ 20 bills and a lot of $5 problems"
Decrease the logistics footprint
The logistics footprint represents the support crews, fuel, parts and ammunition needed to keep a unit operational. Long supply chains, large refueling vehicles and the need to set up large maintenance depots work against agility and makes the forces that they're attached to more vulnerable.
Reduce operating and maintenance costs
Creating multiple units based on the same basic structures allows for exchangeable parts and gives maintenance personnel the ability to repair a wider range of units with the same amount of training. This also contributes to a smaller logistics footprint and greater agility. The Army is focusing on smaller, lighter vehicles that are faster and more maneuverable. Instead of heavy armor, units will use stealth strategies and smaller profiles to reduce casualties. Lighter vehicles are also easier to transport and use less fuel. The Army will combine its efforts with other military branches and other nations. This makes the ability to communicate with coalition forces a vital facet of future warfare.
Increase battlefield lethality and survivability
Tomorrow's soldiers need to destroy their targets and survive attacks a greater percentage of the time. This reduces the number of units needed in any particular engagement, reduces the need for extensive reinforcements and eases the burden on medical and repair units. FORCE WARRIOR:
Wars are evolutionary, with each new conflict bringing more powerful and advanced weaponry. Weapons that yield success on the modern battlefield today can quickly become outdated and ineffective in just a few years. The reality of the battlefield necessitates continuous change in the pursuit to stay a step ahead of the enemy. en emy.
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Future Force soldiers
To better equip its soldiers, the U.S. Army is developing an advanced infantry uniform that will provide superhuman strength and greater ballistic protection than any uniform to date. Also, using wide-area networking and onboard computers, soldiers will be more aware of the action around them and of their own bodies. TETRA VAAL LAW ENFORCING MILITARY ROBOT:
This great video has been gaining some attention on the Internet recently. The concept is believable and to be honest, the implications that we already created an artificial form of life aren’t far off either. But for anyone with some tech know how, or for those who never believe any to-good-to-be-true video clip, it was never a reality, more of a great piece of CGI. Although the human race has yet to come up with something quite so technological advanced, it is clear that in this day and age, it is almost impossible to tell the difference between the computer-generated material and the real footage. And although the idea of a law enforcing military robot is certainly not original, the clip is surely the best and most realistic vision on the future of artificial intelligence we have seen so far. Unmanned Spy Planes EYE IN THE SKY: The Rapid Eye could be sent anywhere around the world in an hour
by traveling inside a ballistic missile and exiting the missile's shell when its destination is reached.The Department of Defense wants to develop spy satellites that can detect a military force mobilizing halfway around the world, enabling it to immediately assess possible threats to national security. An unmanned surveillance aircraft packed into the nose of a missile would be launched over suspicious areas to gather more intelligence; if the threat were confirmed, it would be replaced by another aircraft that could perform low-flying surveillance for up to five years without returning to Earth to refuel. 23
US ARMY TO TEST ARTIFICIAL INTELLIGENCE IN MMOS:
The US Army are working on fake soldiers. That are, to dumb the science down a pinch, holographic projections imbued with artificial intelligence. These fake troops can then be used for stuff like training exercises. Anyway, to test the AI for these holo-soldiers, the Army wants to set them up in games like World of Warcraft and Eve Online. They figure that if the AI - which can be designed to speak in local slang and make human conversation - can pass for human in the online realm, they'll be on the right track. Hopefully the AI doesn't act too human, and end up quitting the army, moving in with its parents and blowing 19 hours a day grinding away on WoW. CONCLUSION:
After reading different articles on military applications of AI we come to know that AI has vast applications some are being implemented as mentioned above in the case study .One of the fact which we came across after reading all the articles is that America is investing a lot in implementing AI in the war one of the reason could be US invasion in Iraq and Afghanistan and the soldiers are dying in war hence US wants some replacement and machines is a very good option .U.S ,China ,Turkey and some other countries are using them in the war .although AI is helping a lot but after reading all the article we have come to a point that AI will be a threat to human life because Despite decades of research in the field of artificial intelligence (AI), computers remain unable to make simple visual discriminations such as picking a cow out of a barnyard scene. Robotic systems would be hard-pressed to tell friend from foe even in ideal conditions .along with this there is also a point that this technology can be in wrong hand .which will be a very large threat to the humans .after analyzing we have also come to a point that all the countries are in a state of race with each other .All the countries spend a huge amount on this.
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RECOMMENDATIONS After analysis of different articles some recommendations are given below:
1. Proposes a global ban on autonomous weapons until they can comply with international rules of war prohibiting the use of force against no ncombatants. 2. Authorizing a machine to make lethal combat decisions is contingent upon political and military leaders resolving legal and ethical questions. These include the appropriateness of machines having this ability, under what circumstances it should be employed, where responsibility for mistakes lies and what limitations should be placed upon the autonomy of such systems. 3. Ai implementation is very expensive ,we should create a harmony and peace among countries so that they would spend these huge amount on the prosperity of their people rather than empowering their military and creating a threat of war. 4. There should be Accountability about how different robots are working .the robots or machines should not be given complete authority. 5. There should be some Legal code of conduct and a limit should be set so that people are not killed without reasons by the machines Example: Aegis defense system shoots down an Iranian Airbus jetliner in 1988.
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REFRENCES
The next 'new frontier' of artificial intelligence
November 1, 2000,By John Rhea
Pentagon Developing New Unmanned Spy Planes
By Larry Greenemeier | September 17, 2007 |
“Will AI in killer military robots lead to real Terminators?” By Layer 8 on 8 on Wed, 08/05/09.Michel Cooney.
Robotics Prof Sees Threat in Military Robots
By JR Minkel | February 28, 2008 |
Robot wars
Published online 8 February 2005 | Nature | doi:10.1038/news050207-7News
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