
AP / Allauddin Khan
A U.S. Army helicopter takes off carrying wounded soldiers, injured in a roadside bomb in Kandahar, Afghanistan, Monday, Aug. 30, 2010.
The ongoing military campaign against Afghan insurgents may get a boost from new computer software designed to zero in on the locations of weapons caches and warlords.
"The idea is to say, look, this is a large area, where do you target your resources," Venkatramanan Subrahmanian, co-director of the Lab for Computational Cultural Dynamics at the University of Maryland, told me today.
The software, called SCARE (Spatio-Cultural Abductive Reasoning Engine), combines data on terrain, road networks, tribal affiliations and past attacks with a computational analysis technique called geospatial abduction to help locate the enemy.
Geospatial abduction is a way to infer unobserved geographic phenomena (such as where explosives are hidden) from a set of known observations and constraints, such as the locations of past attacks and the roads that have been used to move around large caches of bomb-making materials.
Optimized SCARE
SCARE was first used to analyze attacks in Iraq involving IEDs (improvised explosive devices) and predict the locations of IED weapons caches. Subrahmanian's team optimized the second generation of the software for use in Afghanistan.
Applying the technology to Afghanistan presented several new challenges, including the varied terrain, the vast area that had to be covered (360 by 270 miles, or 580 by 430 kilometers), and the influence of multiple tribes.
"There are inter-tribe rivalries, so clearly tribesmen who carry out certain attacks are more likely to want to seek refuge with parties they trust, which happens to be their own tribe," Subrahmanian said. "So we had to understand the geography of the region both in terms of terrain and roads as well as tribal affiliations."
Other constraints on the insurgents include a desire to carry out their attacks near their home bases or weapons caches, but not too close to them.
And since the software is designed to find large weapons caches and high-level insurgent leaders, "We use an assumption to restrict movements of the insurgents to the road," Paulo Shakarian, a US Army Captain and PhD candidate in computer science at the University of Maryland told me.
Zeroing in
In an evaluation of the software's effectiveness in Helmand and Kandahar provinces, it pinpointed the insurgents and their weapons to regions of less than 39 square miles (100 square kilometers), that contained an average of 4.8 villages and a density of high-value targets 35 times greater than in the provinces as a whole.
"What that tells a commander of international security forces in Afghanistan is that four or five villages are the places he can zero in on and bring his other assets to bear," said Subrahmanian.
For example, the commander might decide to get aerial imagery of the villages with an unmanned aerial vehicle (UAV).
"With a UAV, you have to plan out the route, there is only so much fuel, there is only so much of a camera lens to look at things, so you need to be able to reduce the area you are searching for quite a bit in order to make that platform effective," Shakarian noted.
But while the technology helps pinpoint where the insurgents are likely to be found today, won't they just adapt? No, they probably won't, Subrahmanian said, since they are still forced to operate under the same constraints: terrain, roads and tribal affiliations.
"Even if they read our paper, all they know is that we know they have to operate under certain constraints, which they know we know already," he said. "So we don't see this as giving them any kind of advantage of any sort."
What's more, Shakarian added, the software depends on the data input to the system and that information is closely guarded.
Disease detection
In addition to military applications, the technology, which as cost about $300,000 to develop, is being tested for use in identifying animal hosts for certain viruses that spread disease in Africa, Subrahmanian noted.
"The idea is you see where the outbreak occurs and then try to infer back from that locations of the animals that host the viruses that cause the diseases and presumably the public health organizations could look at those regions and decide what action to take," he said.
A paper on SCARE-S2 has been accepted for publication in the 2011 International Conference on Innovative Applications of Artificial Intelligence.
More stories on military software:
- Pentagon seeks billions to battle terror abroad
- Today's G.I.s train with video games
- Computer has eye for suspicious behavior
- Robot warriors will get a guide to ethics
- U.S. Army turns to phone apps to win wars
- Pentagon: Insurgents intercepted spy videos
- Fog of war demystified by financial 'power law'
John Roach is a contributing writer for msnbc.com. Connect with the Cosmic Log community by hitting the "like" button on the Cosmic Log Facebook page or following msnbc.com's science editor, Alan Boyle, on Twitter (@b0yle).


Must the media ALWAYS tip our hand to the enemy?
Do they ALWAYS have to know exactly how we are going to come at them...?
From the article...
It seems that the insurgents would have to completely change their lifestyle to no longer be operating under the same constraints. I.E. They would have to start making serious alliances with tribes they may potentially hate. Stop using the roads. Or just completely move out of their homes.
Isn't this just geographical profiling with a computer ?.That's a technique thats been in use for a number of years with police forces looking for serial murderers & environmental scientist looking for rare species.They analise their subject from general /specific characteristics of behaviour throw in some facts (ie.where the victims lived/where the bodies were found ) plot it all on a map & come up with an educated guess.This is nothing new and its something I suspect the military has been using for sometime.
From the description, it does sound like the same kind of technology, but the scale is much wider. And the constraints in Iraq and Afghanistan Vs. an Urban environment is much more different, and much harder to correlate.
This sounds like how an intelligent military leader would consider his/her options. That is, you gather information about your enemy and try to anticipate what they would do.
The big difference would be that the decision would be impartial. But that would depend on how the various factors are weighted by the programmer.
A failed mission could always be blamed on the computer.
"Adapt and improvise." - Gunny Highway.
It amazes me how a T.V. crew can get in with the Taliban to film them killing NATO troops. How about a "spy" putting a location beacon on one of these reporters that will give us a location and then hit the area with a MOAB. It seems when ever we take on a police action, we have to fight with our hands behind our backs. Either win this with any means possible or get out.
A MOAB seems a little excessive for killing what usually amounts to a 5-10 man team. A cheap hellfire missile seems enough to do the job...
Statistical inference based on real data should work to predict with a given degree of probability the area in which a recurrence in likely to happen. This is a valid use of statistics, and its use in limited only by the computer power available to process the equations and the availability and input of quality data.
At the point where the input data is in any not of high quality (think Viet Nam event inflation here...) then the outputs will become a lot less useful, and maybe even counterproductive.
As the outputs are ONLY probability based; it is important to use other assets to determine if an "event" is really in a particular place or not. It would be nearly impossible in the real world to pre-target weapons systems at high probability concentrations, as a 100% perfect "solution" for a discrete spot is nearly an impossibility.
I'm surprised this kind of thing has not long ago been used in long-term battlefield scenarios where lots of event data is available and the ongoing nature of a war would make such data useful.