A Wargame 55 Years in the Making (Part 3)

The goal of my doctoral research was to create a suite of algorithms that were capable of making ‘human-level’ tactical and strategic decisions. The first step is designing a number of ‘building block’ algorithms, like the least weighted path algorithm that calculates the fastest route between two points on a battlefield while avoiding enemy fire that we saw in last week’s post. Another important building block is Kruskal’s Minimum Spanning Tree algorithm which allows the computer to ‘see’ lines of units.

I use terms like ‘see’ and ‘think’ to describe actions by a computer program. I am not suggesting that current definitions of these terms would accurately apply to computer software. However, it is simply easier to write that a computer ‘sees’ a line of units or ‘thinks’ that this battlefield situation ‘looks’ similar to previously observed battlefields. What is actually happening is that units are represented as nodes (or vertices) in a a graph and some basic geometry is being applied to the problem. Next week we will use probabilities. But, at the end of the day, it’s just math and computers, of course, don’t actually ‘see’ anything.

Examples of how Kruskal's Minimum Spanning Tree algorithm can be used to separate groups of units into cohesive lines. These figures are taken from, "Implementing the Five Canonical Offensive Maneuvers in a CGF Environment." by Sidran, D. E. & Segre, A. M.

Examples of how Kruskal’s Minimum Spanning Tree algorithm can be used to separate groups of units into cohesive lines. These figures are taken from, “Implementing the Five Canonical Offensive Maneuvers in a CGF Environment.” by Sidran, D. E. & Segre, A. M.

When you and I look at a map of a battle we immediately see the opposing lines. We see units supporting each other, interior lines of communication, and lines of advance and retreat. The image, below, shows how the program (in this case, TIGER, the Tactical Inference Generator which was written to demonstrate my doctoral research) ‘sees’ the forces at the battle of Antietam. The thick black line is the ‘MST Spine’. You and I automatically perceive this as the ‘front line’ of the Confederate forces, but this is a visual representation of how TIGER calculates the Confederate front line. Also important is that TIGER perceives REDFOR’s flanks as being anchored (that is to say, BLUE does not have a path to the flanking objective, the tip of the green vector, that does not go through RED Range of Influence, ROI, or Zone of Control).

Figure 1. TIGER screen shot of ‘flanking attribute’ calculations for the battle of Antietam (September 17, 1862, 0600 hours). Note the thick black line that repres ents the MST spine of REDFO R Group 0, the extended vectors th at calculate the Flanking Goal Objective Point and BLUEFOR and REDFOR ROI (red and blue shading). REDFOR (Confederate) has anchored flanks.

TIGER screen shot of ‘flanking attribute’ calculations for the battle of Antietam (September 17, 1862, 0600 hours). Note the thick black line that represents the MST spine of REDFOR Group 0, the extended vector that calculates the Flanking Goal Objective Point and BLUEFOR and REDFOR ROI (red and blue shading). REDFOR (Confederate) has anchored flanks. From, “Algorithms for Generating Attribute Values for the Classification of Tactical Situations,” by Sidran, D. E. & Segre, A. M.

Now that TIGER can see the opposing lines and recognize their flanks we can calculate the routes for implementing the Course of Action (COA) for various offensive maneuvers. U. S. Army Field Manual 3-21 indicates that there are five, and only five, offensive maneuvers. The first is the Penetration Maneuver (note: the algorithms for these and the other maneuvers appear in, “Implementing the Five Canonical Offensive Maneuvers in a CGF Environment.” by Sidran, D. E. and Segre, A. M.) and can be downloaded from ResearchGate and Academia.edu.

The Penetration Maneuver is described in U.S. Army Field Manual 3-21 and as implemented by TIGER. Note how TIGER calculates the weakest point of REDFOR's line. From, "Implementing the Five Canonical Offensive Maneuvers in a CGF Environment." by Sidran, D. E. and

The Penetration Maneuver is described in U.S. Army Field Manual 3-21 and as implemented by TIGER. Note how TIGER calculates the weakest point of REDFOR’s line. From, “Implementing the Five Canonical Offensive Maneuvers in a CGF Environment.” by Sidran, D. E. and Segre, A. M. Click to enlarge.

The next maneuver is the Infiltration Maneuver. Note that to implement the Infiltration Maneuver, BLUEFOR must be able to infiltrate REDFOR’s lines without entering into RED’s ROI:

The Infiltration Maneuver.

The Infiltration Maneuver as described in U.S. Army Field Manual 3-21 and as implemented by TIGER. Note how TIGER reaches the objectives without entering into REDFOR ROI. From, “Implementing the Five Canonical Offensive Maneuvers in a CGF Environment.” by Sidran, D. E. and Segre, A. M. Click to enlarge.

The next maneuver is the Turning Maneuver. Note: in order to ‘turn an enemy’s flanks’ one first must be able to recognize where the flanks of a line are. This is why the earlier building block of the MST Spine is crucial.

The Turning Maneuver as illustrated in U. S. Army Field Manual 3-21 and in TIGER.

The Turning Maneuver as illustrated in U. S. Army Field Manual 3-21 and in TIGER. From, “Implementing the Five Canonical Offensive Maneuvers in a CGF Environment.” by Sidran, D. E. and Segre, A. M. Click to enlarge.

Certainly the most complex offensive maneuver is the Envelopment Maneuver which requires two distinct movements and calculations for the attacking forces: first the attacker must decide which flank (left or right) to go around and then the attacker must designate a portion of his troops as a ‘fixing force’. Think of an envelopment maneuver as similar to the scene in Animal House when Eric “Otter” Stratton (played by Tim Matheson) says to Greg Marmalard (played by James Daughton), “Greg, look at my thumb.” Greg looks at Otter’s left thumb while Otter cold-cocks Marmalard with a roundhouse right. “Gee, you’re dumb,” marvels Otter. In an envelopment maneuver the fixing force is Otter’s left thumb. Its purpose is to hold the attention of the victim while the flanking force (the roundhouse right) sweeps in from ‘out of nowhere’. In the next post I will show a real-world example of an Envelopment Maneuver created by my MATE (Machine Analysis of Tactical Environments) program for DARPA.

The Envelopment Maneuver as shown in U. S. Army Field Manual 3-21 and as implemented in TIGER.

The Envelopment Maneuver as shown in U. S. Army Field Manual 3-21 and as implemented in TIGER. From, “Implementing the Five Canonical Offensive Maneuvers in a CGF Environment.” by Sidran, D. E. and Segre, A. M. Click to enlarge.

Lastly, and obviously the maneuver of last resort, is the Frontal Assault:

The Frontal Assault Maneuver from

The Frontal Assault Maneuver from, “Implementing the Five Canonical Offensive Maneuvers in a CGF Environment.” by Sidran, D. E. and Segre, A. M. Click to enlarge.

All that I’ve done in this post is show some of the things that the TIGER program does. What I haven’t done is show how the algorithms work and that’s because they are described in the papers, below. Obviously, this is a subject that I find pretty interesting, so feel free to ask me questions (you can use the Contact Us page).

It is my intention to incorporate these algorithms into the General Staff wargame. However, I’ve been told by a couple of game publishers that users don’t want to play against a human-level AI. What do you think? If you’ve read this far I would really appreciate it if you would answer the survey below.


Papers that were cited in this post with download links:

“An Analysis of Dimdal’s (ex-Jonsson’s) ‘An Optimal Pathfinder for Vehicles in Real-World Terrain Maps'”

In PDF Format

“Algorithms for Generating Attribute Values for the Classification of Tactical Situations.”

In PDF Format

“Implementing the Five Canonical Offensive Maneuvers in a CGF Environment.”

In PDF Format


 

A Wargame 55 Years in the Making (Part 2)

After The War College I created a couple of non-wargames including Online Mysteries, a massive multiplayer online mystery game that was written for AOL’s WorldPlay. WorldPlay was envisioned to be a 3D online world populated with avatars. It was similar in concept to Second Life but, like a lot of great ideas, was ahead of its time. AOL shut WorldPlay down before most of the games, including Online Mysteries, launched.

Mysteries Unlimited screen shot (Windows) was a massively multiplayer online mystery game created for AOL/WorldPlay (click to enlarge).

Mysteries Unlimited screen shot (Windows) was a massively multiplayer online mystery game created for AOL/WorldPlay (click to enlarge).

By 2000 the game publishing industry  was going through another convulsion of consolidations, buyouts and contractions. Publishers were producing fewer games but the ones that were being created had large teams, long development cycles and massive budgets. The days when an independent developer could pitch a game idea, get an advance and then develop it outside of a publisher’s studio were gone. And the last thing that the big publishers were interested in were wargames.

Over the previous fifteen years I had received inquiries from active duty military and Pentagon project managers about my wargames (known as Commercial Off The Shelf, or COTS, in Pentagon-lingo) and if I would be available to consult on various wargaming projects. Unfortunately, I was lacking a key prerequisite for this: a doctorate. I returned to academia, first to a small local college where I also taught computer game design and in 2003 I was accepted in the computer science PhD program at the University of Iowa (one of the oldest computer science departments in the world).

Before I ever set foot in MacLean Hall (the home of the Department of Computer Science at the University of Iowa) I knew what I would spend the next six years of my life researching and studying: tactical and strategic AI (I would eventually coin the phrase ‘computational military reasoning’ to describe this field).  What I soon discovered was that very little work had ever been done in this research area. What was even more surprising was my discovery that most ‘professional’ military wargames (i.e. wargames used by the US Army, NATO, England, Australia, France, etc.) had absolutely no AI whatsoever. Instead, they employed ‘pucksters’ (usually retired military officers) who made all the moves for OPFOR (Opposition Forces, AKA ‘the enemy’) from another computer in another room.

Pucksters, or humans (usually retired military officers) who make the decisions and moves for enemy (or OPFOR) units during a wargame.

Pucksters are humans (usually retired military officers) who make the decisions and moves for enemy (Opposition Forces = OPFOR) units during a wargame. Note the sign OPFOR & EXCON (Exercise Control) over the puckster’s work station.

To earn a doctorate at an American ‘Research One’ university requires 90 graduate credits (about 30 classes), a GPA > 3.5 (out of 4.0) and passing three major examinations. The first examination on the road to a doctorate is the Qualifying Examination (or Q Exam as everyone calls it). The topic of my Q exam was “An Analysis of Dimdal’s (ex-Jonsson’s) ‘An Optimal Pathfinder for Vehicles in Real-World Terrain Maps’.” This is the area of computer science and graph theory known as ‘least weighted path algorithms’. GPS devices and Map apps use a least weighted path algorithm, except they’re only interested in roads; they don’t consider terrain, slope and other things (that are important to a military unit maneuvering on a battlefield).

Now, if you were to wander into the ivied halls of academic computer science  (like MacLean Hall) and inquire of a tenured faculty member how to calculate the fastest path between two points on a sparse grid they would almost certainly reply to you, “Dijkstra’s algorithm.”  Dr. Dijkstra invented his algorithm in 1956 and it works like this: first calculate the distance between every point on the map and every other point on the map. Then figure out the fastest path. Yeah, it’s that obvious, and painfully slow. In fact, it’s so slow that it isn’t used for GPS or game AI. In computer science we us ‘Big O’ notation to describe how fast (or slow) an algorithm takes to run. Dijkstra’s algorithm runs in O(|V|2). This means that as the number of vertices, or points on the map, (that’s the |V| part) increases, the time it takes for the entire algorithm to complete goes up by the square of the number of vertices. In other words, as the map gets bigger the algorithm gets a lot slower.

Dimdal, and I and most of the gaming world do not use Dijkstra’s algorithm, Instead we use A* (pronounced ‘A Star’) which was designed in 1968 primarily by Nils Nilsson with later improvements by Peter Hart and Bertram Raphael. Below is an example of A* used in General Staff (note that the algorithm doesn’t look at every point on the map, just ones that it thinks are relevant to the problem at hand). A* runs in O(n) time.

A screen shot of A* algorithm running. The green areas are where the algorithm searched for a least weighted path, the brown line is the shortest path (mostly following a road).

A screen shot of A* algorithm running. The green areas are where the algorithm searched for a least weighted path, the brown line is the shortest path (mostly following a road).

Graph showing the difference between Dijkstra's algorithm and the A* algorithm. The blue line that increases rapidly shows that Dijkstra's algorithm gets much slower as the map gets bigger. A* is not affected as much by the size of the map.

Graph showing the difference between Dijkstra’s algorithm and the A* algorithm. The blue line that increases rapidly shows that Dijkstra’s algorithm takes much more time as the map gets bigger. A* (the green line) is not affected as much by the size of the map.

As part of my research into computational military reasoning I made further modifications to A* to take into effect the slope of the terrain (which can affect speed of some units), the range of enemy units (OPFOR ROI, e.g. areas controlled by enemy artillery) and to avoid enemy line of sight (LOS). My MATE (Machine Analysis of Tactical Environments) project used all of these options:

A slide from my presentation to DARPA showing how my modified A* avoids enemy range of weapons.

A slide from my presentation to DARPA showing how my modified A* avoids enemy range of weapons. The likelihood of taking casualties is indicated by the darkness of the red coloring.

While working on General Staff I came up with a new optimization of the A* algorithm which I’ve called EZRoadStar. EZRoadStar first looks at the roadnet and attempts to utilize it for rapid troop movement. Only after ascertaining how far using roads will get it to its goal does the algorithm look for nonroad paths. EZRoadStar is much faster than traditional A*; especially for wargames and military simulations.

An example of the EZRoadStar least weighted path algorithm. What's the fastest way point A to point B (the yellow line)? Taking the road, of course. This algorithm looks at a battlefield like a commander and utilizes the roadnet first before looking at other options. Click to enlarge.

An example of the EZRoadStar least weighted path algorithm. What’s the fastest way from point A to point B (the yellow arrow)? Taking the road, of course. This algorithm looks at a battlefield like a commander and utilizes the roadnet first before looking at other options. Click to enlarge.

Well, this wargame may be 55 years in the making and it looks like describing some of the key things that went into it may take almost as long. Clearly, I’m going to have to continue this story with yet another post. We’ve just barely scratched the surface of my work on wargame AI. The next installment will (hopefully) cover algorithms for ‘the five canonical offensive maneuvers’ (i.e. The Envelopment Maneuver, The Turning Maneuver, Penetration, Infiltration and Frontal Assault. These are the algorithms that are ‘under the hood’ of General Staff. If any of my readers would like to know more about these topics (links to my published papers on the subject or whatever) please drop me a line at Ezra [at] RiverviewAI.com.

 

A Wargame 55 Years in the Making

I was introduced to wargames (Avalon Hill, of course) about 55 years ago when I was seven years old by my buddy Carl Hoffman who lived down the street. Carl and I ended up owning every Avalon Hill wargame and we played them all. Eventually, Carl and his family moved away (I think Carl became a professor at LSU but I can’t confirm that) and I was faced with the grim realization that all of us Grognards inevitably confront: there was nobody to play wargames with.

Tactics II from Avalon Hill. The first wargame I played. What was the first wargame you played?

Tactics II from Avalon Hill. The first wargame I played. What was the first wargame you played?

Over the years I would occasionally find someone interested in playing  (or, more likely, coerce a friend who really had little interest in wargames) to set up a game but rarely would we ever complete a full campaign or battle.  By the late 1970s playing wargames for me was a rare event (the one exception being my good friend from my undergrad college days, Corkey Custer). Then, about this time, I saw an episode of PBS’s NOVA on what was then the infancy of Computer Graphics (CGI). There, flickering on my black & white TV, was what we would eventually call ‘wire frame’ 3D. Wire frame 3D just shows the edges of 3D objects. They are not filled in with a texture (as CGI is done now). Computers just didn’t have the processing power to pull this off back in the late ’70s and ’80s. But, I immediately thought to myself, “this technique could be used to render 3D battlefields!” And that was the spark from UMS: The Universal Military Simulator was born.

Screen capture of the original UMS running in 640 x 400 x 2 resolution in MS DOS. This is an example of wire frame 3D.

Screen capture of the original UMS running in 640 x 400 x 2 resolution in MS DOS. This is an example of wire frame 3D.

By the mid 1980s I was about to graduate with a bachelor’s degree in computer animation and, more importantly, a working demo of UMS. I had hypothesized that one of the biggest selling points of computer wargames was the ability to always have an opponent handy (the artificial intelligence or AI). I borrowed a copy of the Software Writers Market from the library and sent out dozens (maybe even hundreds) of letters and, eventually, papered an entire wall of my apartment with rejection letters from game publishers. But, Dr. Ed Bever, who designed Microprose’s Crusade in Europe, Decision in the Desert and NATO Commander (pretty much the only computer wargames that were out at the time) saw my pitch letter and gave me a call. Microprose wasn’t interested in publishing UMS per se, rather their CEO, “Wild Bill” Stealey, wanted me to come work for Microprose (and they would own UMS). That deal didn’t appeal to me but a short time later, at the 1986 Consumer Electronics Show in Chicago, Ed Bever introduced me to Microprose’s competitors, Firebird/Rainbird. Within 48 hours I had my first game publishing deal.

Crusade in Europe from Microprose (1985) designed by Dr. Ed Bever, originally programming by Sid Meir.

Crusade in Europe from Microprose (1985) designed by Dr. Ed Bever, originally programming by Sid Meir.

UMS sold about 128,000 units and was the #1 game in the US and Europe for a while.

The European Microdealer Top 30 Chart with UMS as #1 with a bullet on the 16 game chart. What other classic games can you find on the charts? (Click to enlarge)

The European Microdealer Top 30 Chart with UMS as #1 with a bullet on the 16-bit game chart. What other classic games can you find on the charts? (Click to enlarge)

Ed Bever helped on the design of UMS II: Nations at War which was an extremely ambitious global wargame that had unprecedented detail and allowed the user to edit numerous variables and equations:

UMS II: Nations at War screen shots from the MS DOS version. Click to enlarge.

UMS II: Nations at War screen shots from the MS DOS version. Click to enlarge.

UMS II screen shot (Macintosh) showing active weather systems.

UMS II screen shot (Atari ST) showing active weather systems.

An example of the numerous variables that the user could adjust in UMS II. Click to enlarge.

An example of the numerous variables that the user could adjust in UMS II.; in this case adjusting the attrition level based on experience for ground units. Macintosh screen shot. Click to enlarge.

UMS II was named “Wargame of the Year” by Strategy Plus magazine and enjoyed strong sales. In many ways it was the ‘ultimate’ in complex wargaming.  It was far more detailed than any other wargame I’ve seen before or since (and that includes my work on DARPA, Department of Defense, US Army, Office of Naval Research and Modeling Simulation Information Analysis Center (MSIAC) wargames. Ironically, it was published by Microprose because they bought out Firebird/Rainbird and with it my publishing contract.

My next wargame, in 1993, was The War College.  We used data from US Geological Survey to create the 3D maps. Again, it was very detailed and allowed the user to edit combat values and featured an interactive hyperlinked history of each scenario (it shipped with Antietam, Austerlitz, Pharsalus and Tannenberg). Unfortunately, our publisher, GameTek, pretty much ceased to exist just as we were about to release this game. To this day I have no idea how many units it sold. We never got a royalty statement.

Screen shot (MS DOS) of the Austerlitz scenario in The War College. Click to enlarge.

Screen shot (MS DOS) of the Austerlitz scenario in The War College. Click to enlarge.

The War College also had an interactive history for each battle (screen shot from MS DOS, click to enlarge).

The War College also had an interactive history for each battle (screen shot from MS DOS, click to enlarge).

The War College allowed users to adjust melee effectiveness and values. MS DOS screen shot, click to enlarge.

The War College allowed users to adjust melee effectiveness and values. MS DOS screen shot, click to enlarge.

I also would be terribly remiss if I did not mention my good friends who worked on various ports of the above mentioned games, Ed Isenberg (Amiga and MS DOS), Andy Kanakares (Apple IIGS and MS DOS) and Mike Pash (MS DOS).

(left to right) Ed Isemberg, Andy Kanakares, Ezra Sidran. Not pictured; Mike Pash.

(left to right) Ed Isemberg, Andy Kanakares, Ezra Sidran. Not pictured; Mike Pash.

One of the problems of getting old is that your stories get longer to tell. This blog post is far longer than I intended and we haven’t even got to this century and all my research into computational military reasoning (Tactical and Strategic AI) and my new wargame, General Staff.  I’m afraid we’ll have to end this here and pick up the story in Part 2 next week.

First Survey Results!

The results of our first survey about what kind of wargame you would like to see are now available and there were plenty of surprises. The first question that we asked you was: did you prefer a 2D or 3D game. I had been previously assured by the, “largest digital publisher of wargames in the world,” that only 3D games would sell. But, that doesn’t seen to be upheld by these results:

Survey question #1: 2D or 3D wargame? 29% said 3D, 39% said 2D and 32% said 'It didn't matter."

Survey question #1: 2D or 3D wargame? 29% said 3D, 39% said 2D and 32% said ‘It didn’t matter.”

Surprisingly, 71% of respondents said that they would either be happy with a 2D wargame or that it didn’t matter to them. Those are pretty overwhelming numbers. It should be no surprise that it takes a great deal more time and money to create a 3D wargame than a 2D wargame so these results are quite eye opening and also reassuring. While this flies in the face of what we were told by the ‘largest publisher of digital wargames in the world’ it nonetheless, comes directly from the consumers themselves.

The next question was, “How important is the ability to create new scenarios?” Two of the last three games that I wrote (UMS and UMS2) provided the ability for users to create new scenarios. Creating a suite of scenario editing utilities is not trivial. Frankly, as a game designer, you normally just cobble some system together that will allow you to create scenarios for your game. Often these include XAML files and using PhotoShop or some other paint program. Frequently this system is buggy or you have to do something in a weird order for it work right. But when you create an editing suite for the public it has not only be bug-free but it has to have an intuitive and easy to use interface. Based on the your responses, below, it looks like I’ll be creating an editing suite for you to create your own scenarios.

How important is the ability to create new scenarios? 25% said "Very important," 48% said "Somewhat important" and 29% said, "Not very important."

How important is the ability to create new scenarios? 25% said “Very important,” 48% said “Somewhat important” and 29% said, “Not very important.”

The next survey question asked how many scenarios you would like to see ship with the game. The overwhelming favorite was ’20’ and so we’ll make sure that at least 20 scenarios are included.

The overwhelming favorite was 20 scenarios.

The overwhelming favorite was 20 scenarios.

Since 1986 every game that I’ve designed and written has been published by a ‘big’ computer game publisher. Game publishers traditionally give the game developer an advance against royalties and are responsible for distribution and promotion of the product. In return, they take between 50% and 85% of the gross receipts. Yes, that is correct.

The alternative to going the publisher route is to use Kickstarter to self fund and I am very gratified to see that the overwhelming majority of survey respondents said that they would, indeed, support this wargame via Kickstarter:

Respondents to the survey overwhelmingly said they would support a Kickstarter campaign to fund this wargame.

Respondents to the survey overwhelmingly said they would support a Kickstarter campaign to fund this wargame.

The final question in the survey was the all important, “How much would you pay for this wargame?” It looks like a list price of $50 seems not unreasonable. Early backers in Kickstarter always get a price break for their support. I’m thinking $40 on Kickstarter, $50 after.

$50 was the most popular price for this wargame.

$50 was the most popular price for this wargame.

Many thanks to all who participated in this survey (N = 168). The results were surprising and very helpful. Unfortunately, I realized that there are more questions that need to be asked about gameplay and distribution, so expect another survey shortly.

Please Help Us Out By Taking This Survey

We need to know what kind of a computer wargame you would like to see. Should it be 2D or 3D? Do you want the ability to create your own maps, armies and scenarios? Would you support a Kickstarter campaign? How many scenarios would you like to see ship with the game? The following survey will only take a few minutes of your time and your answers are vitally important to us.

 

Rules for Artillery

Screen shot of the page describing the rules for artillery in General Staff.

Screen shot of the page describing the rules for artillery in General Staff.

The special, “proof of concept” demo that we’ve been working for a ‘very well known computer wargame publisher’ is coming along very well and we wanted to share this screen capture of the Special Artillery Rules page. This also will give you a glimpse into how artillery will be used in the game.

As always, comments, critiques (and catching typos!) are always welcome!

The Fog of War

A key element of General Staff gameplay is the notion of ‘fog of war’. In essence we keep three maps: what blue thinks the situation is, what red thinks the situation is and where all units actually are on the map.

A courier reports that an enemy unit was observed four minutes ago. Note: the enemy unit has almost certainly moved on since then. (Click to enlarge.)

A courier reports that an enemy unit was observed four minutes ago. Note: the enemy unit has almost certainly moved on since then. (Click to enlarge.)

Location of your headquarters (HQ) unit is vitally important in General Staff. If an enemy (or friendly) unit is not directly observable to your HQ unit, the information of an enemy unit sighting is passed to HQ via courier. The amount of time for the courier to travel from the observing unit to the HQ is precisely calculated (see screen capture, above). Friendly units report their position every hour and dispatch a courier to HQ with this information as well. The time for a courier to travel from the reporting unit to travel to HQ is also calculated.

In essence, then, locating your HQ unit on a hill, ridge or other prominent feature is important if you want a clear view of the battlefield. Otherwise, you will be dependent on your couriers to penetrate the fog of war.

The phrase, ‘Fog of War’ (or Nebel des Krieges in German) was first written by Carl von Clauswitz in his famous treatise, On War (in 1832, first English translation in 1873):

War is the realm of uncertainty; three quarters of the factors on which action in war is based are wrapped in a fog of greater or lesser uncertainty. A sensitive and discriminating judgment is called for; a skilled intelligence to scent out the truth.

— Carl von Clausewitz

Update: some readers at Kriegsspiel Forum have quite correctly pointed out that at great distances units would certainly not be able to ascertain the name of the unit that they are observing. Consequently, we have changed the information provided to this:

Dispatch from observing unit modified to include distance and just unit type. (Click to enlarge.)

Dispatch from observing unit modified to include distance and just unit type. (Click to enlarge.)

Now the question arises: how far could you see with a 19th century telescope? Do we need to include a maximum range for line of sight? Interesting question. Would like to hear your comments.