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Conflict simulation, peacebuilding, and development

Tag Archives: agent-based modelling

simulations miscellany, Connections diaspora edition

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The Connections 2013 interdisciplinary wargaming conference is currently underway, and I know that several PAXsims readers who weren’t able to travel to Dayton, Ohio are, like me, following it all by VTC or dial-in. For those of you who are interested in listening in, it may not be too late to contact Tim Wilkie for the remote connection information. You can also find the conference presentation slides here, and we’ll also try to recruit some participants to send in their own impressions.

The Connections conference extends through to July 25.

Meanwhile, in other conflict simulation and serious games related news:

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John Curry at the History of Wargaming project discusses why the UK Conference of Wargamers is the best model for a conference—and the worst.

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The folks at MMOWGLI have prepared a couple of papers for the  NPS Acquisition Research Symposium, 2013, focusing on Innovating Naval Business Using a War Game and Improving DoD Energy Efficiency: Combining MMOWGLI Social-Media Brainstorming With Lexical Link Analysis (LLA) to Strengthen the Defense Acquisition Process.

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The latest issue of the Journal of Simulation 7, 3 (August 2013) is out, devoted to agent-based modelling. Of particular interest is an article by Xavier Rubio-Campillo, Jose María Cel, and Jose María and Francesc Xavier Hernández Cardona of the Barcelona Supercomputing Centre and Universitat de Barcelona. In it they used agent-based modelling to examine the development of new infantry tactics during the early eighteenth century—a rare application of this computational technique to military history:

Computational models have been extensively used in military operations research, but they are rarely seen in military history studies. The introduction of this technique has potential benefits for the study of past conflicts. This paper presents an agent-based model (ABM) designed to help understand European military tactics during the eighteenth century, in particular during the War of the Spanish Succession. We use a computer simulation to evaluate the main variables that affect infantry performance in the battlefield, according to primary sources. The results show that the choice of a particular firing system was not as important as most historians state. In particular, it cannot be the only explanation for the superiority of Allied armies. The final discussion shows how ABM can be used to interpret historical data, and explores under which conditions the hypotheses generated from the study of primary accounts could be valid.

Also of interest is previous work by these researchers on using agent-based models to support battlefield archaeology and using spatial analysis to better understand combined arms warfare in the Spanish Civil War.

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33AA651E-C639-481A-97EA-15E537446268_mw1024_n_sOne of the challenges that agent-based modellers have not yet turned their analytical attentions to is how to prevent Russian all-girl punk bands from conducting protests in Russian Orthodox churches. Fortunately, that challenge has been taken up by some Russian programmers, who have released the game Don’t Let Pussy Riot Into The Cathedral. According to Radio Free Europe/Radio Liberty:

A video game was showcased at a recent Russian Orthodox youth festival in Moscow that encourages players to “kill” members of the feminist punk-rock collective Pussy Riot.

In the game, “Don’t Let Pussy Riot Into The Cathedral,” players use an Orthodox cross to snuff out the balaclava-clad women before they enter a domed white church.

Throughout the game, Pussy Riot’s “Punk Prayer For Putin,” which some of them performed in Moscow’s Christ the Savior Cathedral in February 2012, earning three of them jail terms, plays in the background.

When the Pussy Rioters enter the church in the game, they reappear atop the church with horns on. The building gradually falls into disrepair and ominous clouds gather.

A version of the game, which used the name “Inquisition,” was posted online late last year.

I think almost all of the press reporting on this has it completely wrong—the game is clearly satirical, as evidenced by the overweight priests, luxury car, absolutions for sale, and the expensive watch that serves as the load screen (a reference to this). If the game was on display at the youth festival, either someone didn’t understand the humour or it was a very clever piece of performance art.

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At his Sources and Methods blog, Kris Wheaton (Mercyhurst University) discusses Hnefatafl, the ancient Viking game Every intelligence professional should play:

1001689_277186405754085_2142739834_nToday, only dedicated tabletop gamers have ever heard of it and many of them have never had a chance to play the game.  That is a shame for it’s an extraordinary game with a number of lessons embedded in it for the curious intelligence professional.  For example:

  • It is an asymmetric game.  As you can see from the board above, one side starts in the center and the other side surrounds it on all four sides.  One side outnumbers the other by about 2:1.  The sides even have different victory conditions (the player with the pieces in the center need to get the “King”, the large playing piece in the middle of the board, to one of the corners.  The other player is trying to capture the King).  It is not too hard to see a game such as this one incorporated into courses, classes or discussions of asymmetric warfare.
  • It is a conflict simulation.  Most historians agree that there were relatively few large-scale battles involving Vikings. Instead, most of the time, combat resulted from raiding activities.  Hnefatafl seems to reflect the worst case scenario for a Viking raider:  Cut off from your boats and outnumbered 2:1.
  • It provides a deep lesson in strategic thinking.  Lessons in both the strategy of the central position (hundred of years before Napoleon made it famous) and in the relative value of interior vs. exterior lines of communication are embedded in this game.

What makes this game even more fascinating for me is what it teaches implicitly – that is, what are the lessons it teaches the players without the players knowing that they are learning?  Furthermore, what does this tell us about the Viking culture?

But wait, there’s more! Kris will be producing a version of the game through his new company, Sources and Methods Games—a version featuring Vikings and… Cthulhu.

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Every wargamer needs a laser pointer. It is essential when discussing a map, and useful for those lengthy powerpoint presentations during the briefing and debriefing. Miniature gamers often use them to confirm line of sight on the table-top battlefield. Boardgamers can use them to keep the cat away.

Given that.. what could be cooler than pointers that look like sharks… with frickin’ laser beams attached to their heads? Available at ThinkGeek.

Agent-based modelling and the US troop surge in Afghanistan

The latest issue of the Journal of Defense Modeling and Simulation 9, 2 (April 2012) is now out. Most of it is devoted to technical discussions of “Resuability, Interoperability and Composability in Air Warfare Simulations,” but it does also feature an interesting and well-written piece by John Sokolowski, Catherine Banks, and Brent Morrow on “Using an agent-based model to explore troop surge strategy.”

In October of 2001, the United States invaded Afghanistan and replaced the Taliban government. Since its overthrow, the Taliban has pieced together and waged an insurgency to retake Afghanistan, and that insurgency has gained momentum and grown in strength while the United States/North Atlantic Treaty Organization (NATO) effort shrank in size to about 55,000 troops in 2007. A wide range of factors contributed to the insurgency, ranging from socio-cultural to economic to political. This research applied an in-depth study of Afghanistan to an agent-based model to determine if a military troop surge emphasizing a focused security effort could be successful in battling the growing insurgency within Afghanistan. An agent-based model was created and validated against the strategy and situation on the ground in Afghanistan that existed in 2007. Three experiments were conducted representing surges of 50%, 200%, and 400%. The results indicated that a surge of 200% or greater of the existing size force would be necessary to reduce the size of the insurgency, but that a surge of only 50% (50,000 more troops) would not bring about any significant changes as compared to the existing strategy. These model results provide insight into the potential success of various sized troop surges in Afghanistan that implement a focused security effort.

The piece is, unfortunately, behind a paywall, so you’ll need a subscription to JDMS to access the while thing. The core political-military dynamics of their model, however, are captured in the diagram on the right (click to enlarge). These in turn provide the context for the pseudo-tactical model, in which the insurgent and coalition agents fight it out, with detection ranges, a version of the usual Ph and Pk (probability of hits and kills), and probabilities of collateral damage (which in turn affect local attitudes) all modelled. Unlike some of the work done in the technical M&S field, the piece is written in language that is likely to be clear and accessible to those working in very different, non-quantitative areas.

A number of questions might be raised about the model that the authors have developed. One could endlessly quibble about the key variables they have identified, and in some cases whether the relationships always have the directional values they impute to them (for example, deployment of the Afghan National Army—and even more the highly corrupt Afghan National Police, which they don’t model—can sometimes have negative effects on local attitudes, in cases where they are either seen as abusive and predatory, or because they attract Taliban attacks in areas that might otherwise be quiet). However, those criticisms hold true for any game design, and in general my own general reading of conflict dynamics in Afghanistan suggests that quite a bit of it sounds intuitively right.

The authors do validate their model, using open source reporting of changes in Taliban numbers and adjusting the model until it fits the historical record. I’m not sure that their estimates of insurgent “density” are robust enough to provide much validation, however. Moreover, to increase calibration they manipulate only a few of the variables and relationships in the model in order to provide a match against this single indicator. To my mind, that doesn’t provide very strong validation of the underlying model itself.

The simulation attempts to draw conclusions about the relationship between an increase in coalition troop strength in Afghanistan (“the surge”) and the strength of the insurgency. In this, the authors are refreshingly realistic about the limits of agent-based modelling in illuminating policy questions (emphasis added):

The purpose of this study was to provide a means of assessing if the implementation of a military troop surge designated toward a focused security effort strategy might reverse the trend of the growing insurgency in Afghanistan. The strategy using the United States/coalition/Afghan National Army troop strength of about 101,000 soldiers has failed to defeat or even stop the growth of the Neo-Taliban insurgency. This research sought to add some insight into whether or not a surge with a specific role could work within Afghanistan.

…The results of these experiments indicated that a surge of 400,000 or 200,000 troops will reduce the size and strength of the insurgency, but a surge of 150,000 troops would not. These results are not definitive or absolute, but give insight into the possible outcomes of a surge of the given size based on a model built using careful research. This research represents a tool for analysis in the decision process to determine if a surge should occur. It is not the answer to the question of whether a surge would be effective.

In my view, however, they’ve both overstated and understated the value of their analysis. Given the great many assumptions built into the model, I’m even more doubtful than they appear to be that the outcome of the experiment provides useful policy guidance. On the other hand, I think they could do far more to highlight the potential contribution of the experiment as a heuristic device—that is, as a way of helping decision-makers think about a large, complex, wicked problem. As Gary once put it, the article would be even more interesting for a broader audience interested in insurgency and counterinsurgency  if there was less seer and more sage in its approach to the material. The model might offer some insight, for example, in why a limited surge might not work; what key indicators and metrics might be useful in assessing the effectiveness of increased coalition troop strength; or even what variables or nodes seems to have an especially important effect on outcomes. In other words, I think the article would be all the more interesting if rather than simply reporting experimental results, it also highlighted what the construction of the model itself may suggest about conflict dynamics (or our understanding of conflict dynamics) in Afghanistan. It would have also have been useful to report some of the more detailed simulation findings about how particular variables changed under different coalition troop strengths, or which relationships other than troop strength seemed to be most important to outcome.

Still, for the many readers of PAXsims who are interested in such issues but are rarely exposed to either agnet-based modelling or work in the M&S community on political-military issues, it is certainly worth a read.

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