Category Archives: Fog of War

A Game of Birds & Wolves

Commander Roberts going over the lessons learned from “The Game.” Photo from, “A Game of Birds and Wolves,” by Simon Parkin.

Simon Parkin’s A Game of Birds and Wolves: The Ingenious Young Women Whose Secret Board Game Helped Win World War II, tells the fascinating story of a wargame created during the height of the U-Boat Atlantic campaign to be used as a testbed for discovering new anti-submarine tactics. In early 1941, when German wolf packs were destroying Allied shipping at a devastating rate, British Naval Commander Gilbert Roberts was taken out of retirement and personally ordered by Winston Churchill to, “Find out what is happening and sink the U-boats.”

Roberts was given the top floor of the Western Approaches HQ in Liverpool and a small group of WRENs (Women’s Royal Naval Service) as assistants to invent tactics that would counter the enemy wolf packs. His project would be called the Western Approaches Tactical Unit (WATU). (The Western Approaches HQ in Liverpool is now a museum and I can’t wait to visit it when this pandemic is over and General Staff is finished.)

The WATU project – known simply as, “The Game,” – is not the first example of a wargame used as a testbed to discover and improve combat maneuvers. Indeed, Scotsman John Clerk, wrote, An Essay on Naval Tactics: Systematical and Historical in 1779 after using, “…a small number of models of ships which, when disposed in proper arrangement, gave most correct representations of battle fleets… and being easily moved and put into any relative position required, and thus permanently seen and well considered, every possible idea of a naval system could be discussed without the possibility of any dispute.” Using these models Clerk proposed the tactic of “cutting the line,” that Nelson employed at Trafalgar1) Nelson would quote from Clerk’s essay in his famous Trafalgar Memorandum.

When Roberts reported to Sir Percy Noble, commander of Western Approaches he explained that he intended to, “develop a game that would enable the British to understand why the U-boats were proving so successful in sea battles and facilitate the development of counter-tactics… The game would become the basis for a school, where those fighting at sea could be taught the tactics. With a few adjustments.. [the] wargame could be used for either analysis or training.”2)A Game of Birds and Wolves, p. 143 Not surprisingly, Roberts was met with skepticism and not a little bit of derision. As one who is constantly pitching the importance of wargames to the U. S. military I understand the uphill fight that Roberts was facing. British destroyer commanders definitely did not want to go to Liverpool to, “play a game.” But, since the orders had come directly from Churchill, Noble had little choice but to give Roberts the top floor of the Western Approaches HQ for his ‘game’. Roberts made a tactical mistake by referring to WATU’s ‘product’ (in modern bureaucratic parlance) as a ‘game’. I learned this early on in my career: never say the word ‘game’ if it can be avoided. Call what you’re working on a ‘simulation’. Chess is a game. Risk is a game. But I write simulations; and clearly what Roberts was working on was a simulation, too. (That said, the phrase, “game it out,” has now passed into the common idiom and is synonymous with ‘simulation’.)

WATU simulated Fog of War by requiring the users to view the board through peep holes cut in canvas drapes. Submarine tracks (see above) were drawn in green chalk which, apparently, was not visible from the other side of the canvas sheets. The photo shows British destroyer commanders playing, “The Game,” and learning from the simulation. Photo from, “A Game of Birds and Wolves.”

In order to simulate Fog of War Roberts invented a system in which the destroyer commanders would view the board from behind a canvas sheet; their view of the battle restricted by peep holes cut in the canvas. Furthermore, submarine tracks were drawn with green chalk on the floor (see above photo) which, somehow, became invisible when viewed from the other side of the canvas. Consequently, the destroyer commanders had only a restricted view of the battle around them and were completely in the dark as to the simulated U-boats positions.

When Roberts began his work nobody in the British Admiralty knew U-boat tactics. Indeed, the German U-boat commanders were creating their tactics on the fly often ignoring the Kriegsmarine’s Memorandum for Submarine Commanders to fire torpedoes at no closer than 1,000 meters. U-boat ace, Otto Kretschmer was the first to insist that the most efficient way to attack convoys was to slip inside the destroyer screen, launch torpedoes at a range of about 500 meters, submerge and wait for the convoy to pass over them to make his escape ‘out the back’ of the convoy. Interestingly, this was the same technique that I discovered playing Sierra On Line’s  Aces of the Deep.

One of the first scenarios that Roberts investigated using his new wargame was the battle of Convoy HG 76. This was a multi-day contest involving 32 merchant ships, 24 escorts and 12 U-boats. It was considered a great Allied victory because five U-boats were sank (though the Allies only knew of three at the time) and 30 merchant ships made it home safely. Assisted by WRENs Jean Laidlaw and Janet Okell, they replayed the historical situation hoping to understand Allied commander Captain Frederick John “Johnnie” Walker’s anti-submarine maneuver ‘Buttercup’. The Buttercup maneuver (named after Walker’s pet name for his wife) involved, “on the order Buttercup… all of the escort ships would turn outward from the convoy. They would accelerate to full speed while letting loose star shells. If a U-boat was sighted, Walker would then mount a dogged pursuit, often ordering up to six of the nine ships in his [escort] group to stay with the vessel until it was destroyed.”3)A Game of Birds and Wolves, p. 155

What confused Roberts was that the Allied merchant Annavore was torpedoed while in the center of the convoy. As he and the WRENs replayed the scenario they could not duplicate reality unless the U-boat had, “entered the columns of the convoy from behind. And it must have done so on the surface, where it was able to travel at a faster speed than the ships. By approaching from astern, where the lookouts rarely checked, the U-boat would be able to slip inside the convoy undetected, fire at close range, then submerge in order to get away.”4)The Game off Birds and Wolves. P. 158

Using the scenario of when the escorts actually sank a U-boat using the Buttercup maneuver it was determined that they had succeeded by only accidentally hitting a U-boat that was joining the attack on the convoy and not the actual U-boat who had made the attack that they were pursuing. This makes sense when you realize that the attacking U-boat had submerged immediately after the attack and was waiting for the remaining convoy to pass overhead while the escorts were running far outside the perimeter of the convoy looking for it.

In other words, Walker’s Buttercup maneuver was, in fact, a terrible anti-submarine tactic.

The ‘Raspberry Maneuver’, created from numerous runs of ‘The Game’ was determined to an effective anti-submarine tactic. Here it is drawn by Admiral Usborne. From the book, “A Game of Birds and Wolves.” Click to enlarge.

The first successful anti-submarine tactic to be invented using the Game as a test bed was, “Raspberry,” (so called by Wren Ladlaw as a ‘raspberry‘ to Hitler). As you can see from the above drawing, upon discovery of a U-boat or a torpedo hit, the escorts draw closer to the convoy, not the opposite as in Walker’s Buttercup maneuver. When Roberts and the WRENs ran a scenario for Western Approaches commander Noble and his staff, Noble – who at first was highly skeptical – was so impressed that he immediately sent a message to Churchill, “The first investigations have shown a cardinal error in anti-U-boat tactics. A new, immediate and concerted counter-attack will be signaled to the fleet within twenty-four hours.” 5)The Game of Birds and Wolves, p. 162 By summer of 1942, using these new maneuvers, U-boat losses had quadrupled. Eventually other anti-U-boat maneuvers were also developed by the WATU team and all Atlantic destroyer commanders were ordered to WATU to play, “The Game,” and learn the lessons.

Obviously, there were other improvements in anti-submarine warfare that also contributed to the Allies winning the Battle of the North Atlantic. Nonetheless, it is interesting to read about the proper application of simulations in wartime. I have long been an advocate of simulations to test, “what if” scenarios. Indeed, this has been the main focus of my professional career for thirty plus years. It’s still an uphill battle.

References   [ + ]

2. A Game of Birds and Wolves, p. 143
3. A Game of Birds and Wolves, p. 155
4. The Game off Birds and Wolves. P. 158
5. The Game of Birds and Wolves, p. 162

Fog of War

Carl von Clausewitz painted by Karl Wilhelm Wach. Credit Wikipedia. Click to enlarge.

Carl von Clausewitz in his On War wrote, “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.” Though Clausewitz never specifically wrote the phrase ‘Fog of War’, the above quote is the source of the term which we abbreviate today as FoW. FoW in the 18th and 19th centuries (the era specifically covered by General Staff: Black Powder) was especially problematic because of the lack of modern day battlefield information gathering techniques such as drones, aircraft and satellites (yes, hot air balloons were used in the Civil War but their actual value during combat was minimal).

General Staff is a wargame that can simulate the FoW experienced by an 18th or 19th century commander and his staff. We use the qualifier ‘can simulate’ because General Staff can run in five different ‘modes’:

  • Game mode / No Fog of War
  • Game mode / Partial Fog of War
  • Simulation mode / No Fog of War
  • Simulation mode / Partial Fog of War
  • Simulation mode / Complete Fog of War

Game mode came from a strong desire to create an introductory wargame, with simplified rules, played on historical accurate battlefield maps that could be used to introduce novices to wargaming.

1st Bull Run, 11:30 AM, Simulation Mode, No Fog of War. Reinforcements shown. Click to enlarge.

Antietam, 0600, Game Mode. Reinforcements shown. Click to enlarge.

In the above two screen shots from General Staff you can clearly see the differences between Simulation and Game mode. In Simulation mode a unit’s exact strength in men, leadership value, morale value, experience value, number of volleys and the time it will take for a courier to travel from it’s commander’s HQ to the unit are displayed and tracked. In Game Mode, unit strength is represented by the number of icons (1 – 4) and leadership, morale, experience, and ammunition are not tracked. Units are moved directly by the player and there are no HQ units. In Simulation Mode, orders are given from the commanding HQ down to the subordinate commander’s HQ and then to the actual unit. The leadership value of each HQ effects how long the orders will be delayed on the way.

Little Bighorn, Simulation Mode, Complete Fog of War (from the commander’s perspective). Screen shot. Click to enlarge.

In the above screen shot, we see ‘Complete Fog of War’; only what the commander can see of the battlefield is displayed. In this case, this is what Colonel George Custer could see at this time.  Just as in real life, in Complete Fog of War the commander receives dispatches from his troops about what they have observed; but this information is often stale and outdated by the time it arrives.

Little Bighorn, Simulation Mode, Partial Fog of War. This displays what all Blue forces can observe. Click to enlarge.

In the above screen shot Partial Fog of War is displayed. This is the sum of what is observable by all units (in this case, the Blue force). This is historically inaccurate for the 19th century and is included as an option because, frankly, users may want it and, programmatically, it was an easy feature to add. Throughout the development of General Staff we have consistently offered the users every conceivable option we can think of. That is also why we have included the option of, “No Fog o War,” with every unit visible on the battlefield. It’s an option and some users may want it.

We have experimented with different ways of displaying ‘stale’ unit information including this method, below:

An example of how units that are not directly visible to HQ are displayed. The longer that a unit remains unobserved, the fainter it becomes. (Click to enlarge.)

We are now experimenting with overlays.

As always, your questions and comments are appreciated. Please feel free to email me directly.

Antietam & AI

MATE AI selected Objectives for Blue, 3D Line of Sight (3DLOS) and Range of Influence (ROI) displayed for the Antietam: Dawn General Staff scenario. Screen shot from General Staff Sand Box. Click to enlarge.

The author walking across Burnside’s Bridge in 1966 (age 12).

I have been thinking about creating an artificial intelligence (AI) that could make good tactical decisions for the battle of Antietam (September 17, 1862, Sharpsburg, Maryland) for over fifty years. At the time there was little thought of computers playing wargames.1)However, it is important to note that Arthur Samuel had begun research in 1959 into a computer program that could play checkers. See. “Samuel, Arthur L. (1959). “Some Studies in Machine Learning Using the Game of Checkers”. IBM Journal of Research and Development.” What I was envisioning was a board wargame with some sort of look-up tables and coffee grinder slide rules that properly configured (not sure how, actually) would display what we now call a Course of Action (COA), or a set of tactical orders. I didn’t get too far on that project but I did create an Antietam board wargame when I was 13 though it was hardly capable of solitaire play.

The Antietam scenario from The War College (1992). This featured 128 pre-rendered 3D views generated from USGS Digital Elevation Model Maps.

In 1992 I created my first wargame with an Antietam scenario: The War College (above). It used a scripted AI that isn’t worth talking about. However, in 2003 when I began my doctoral research into tactical AI I had the firm goal in my mind of creating software that could ‘understand‘ the battle of Antietam.

TIGER Analysis of the battle of Antietam showing Range of Influence of both armies, battle lines and RED’s avenue of retreat. TIGER screen shot. Appears in doctoral thesis, “TIGER: A Machine Learning Tactical Inference Generator,” University of Iowa 2009

The TIGER program met that goal (the definition of ‘understand’ being: performing a tactical analysis that is statistically indistinguishable from a tactical analysis performed by 25 subject matter experts; e.g.. active duty command officers, professors of tactics at military institutes, etc.).

In the above screen shot we get a snapshot of how TIGER sees the battlefield. The darker the color the greater the firepower that one side or the other can train on that area. Also shown in the above screen shot is that RED has a very restricted Avenue of Retreat; the entire Confederate army would have to get across the Potomac using only one ford (that’s the red line tracing the road net to the Potomac).  Note how overlapping ROIs cancel each other out. In my research I discovered that ROIs are very important for determining how battles are described. For example, some terms to describe tactical positions include:

  • Restricted Avenue of Attack
  • Restricted Avenue of Retreat
  • Anchored Flanks
  • Unanchored Flanks
  • Interior Lines
  • No Interior Lines

A Predicate Statement list generated by MATE for the battle of Antietam.

Between the time that I received my doctorate in computer science for this research and the time I became a Principal Investigator for DARPA on this project the name changed from TIGER to MATE (Machine Analysis of Tactical Environments) because DARPA already had a project named TIGER. MATE expanded on the TIGER AI research and added the concept of Predicate Statements. Each statement is a fact ascertained by the AI about the tactical situation on that battlefield. The most important statements appear in bold.

The key facts about the tactical situation at Antietam that MATE recognized were:

  • REDFOR’s flanks are anchored. There’s no point in attempting to turn the Confederate flanks because it can’t be done.
  • REDFOR has interior lines. Interior lines are in important tactical advantage. It allows Red to quickly shift troops from one side of the battlefield to the other while the attacker, Blue, has a much greater distance to travel.
  • REDFOR’s avenue of retreat is severely restricted. If Blue can capture the area that Red must traverse in a retreat, the entire Red army could be captured if defeated. Lee certainly was aware of this during the battle.
  • BLUEFOR’s avenue of attack is not restricted. Even though the Blue forces had two bridges (Middle Bridge and Burnside’s Bridge) before them, MATE determined that Blue had the option of a wide maneuver to the north and then west to attack Red (see below screen shot):

MATE analysis shows that Blue units are not restricted to just the two bridge crossings to attack Red. MATE screen shot.

  • BLUEFOR has the superior force. The Union army was certainly larger in men and materiel at Antietam.
  • BLUEFOR is attacking across level ground. Blue is not looking at storming a ridge like at the battle of Fredericksburg.

MATE AI selects these objectives for Blue’s attack. General Staff Sand Box screen shot. Click to enlarge.

We now come to General Staff which uses the MATE AI. General Staff clearly has a much higher resolution than the original TIGER program (1155 x 805 terrain / elevation data points versus 102 x 66, or approximately 138 times the resolution / detail). In the above screen shot the AI has selected five Objectives for Blue. I’ve added the concept of a ‘battle group’ – units that share a contiguous battle line – which in this case works out as one or two corps. Each battle group has been assigned an objective. How each battle group achieves its objective is determined by research that I did earlier on offensive tactical maneuvers 2)See, “Implementing the Five Canonical Offensive Maneuvers in a CGF Environment.” link to paper.

As always, I appreciate comments and questions. Please feel free to email me directly with either.

References   [ + ]

1. However, it is important to note that Arthur Samuel had begun research in 1959 into a computer program that could play checkers. See. “Samuel, Arthur L. (1959). “Some Studies in Machine Learning Using the Game of Checkers”. IBM Journal of Research and Development.”
2. See, “Implementing the Five Canonical Offensive Maneuvers in a CGF Environment.” link to paper.

Wargame AI Continued: Range of Influence

In two previous blogs I wrote about how Artificial Intelligence (AI) for wargames perceive battle lines and terrain and elevation. Today the topic is how computer AI has changed ‘Range of Influence’  (ROI) or ‘Zone of Control’ (ZOC) analysis. Range of Influence  and Zone of Control are terms that can be used interchangeably. Basically, what they mean is, “how far can this unit project its power.”

One of the first appearances of range as a wargame variable was in Livermore’s 1882 American Kriegsspiel: A Game for Practicing the Art of War Upon a Topographical Map (superb article on American Kriegsspiel here).  Note that incorporated into the ‘range ruler’ (below) is also a linear ‘effectiveness scale’.

Detail of Plate IV, “The Firing Board,” from the American Kriegsspil showing a ruler for artillery range printed on the top. Note the accuracy declines (apparently linearly) proportional to the distance. Click to enlarge.

The introduction of hexagon wargames (first at RAND and then later by Roberts at Avalon Hill; see here) created the now familiar 6 hexagon ‘ring’ for a Zone of Control:

Zone of Control explained in the Avalon Hill Waterloo (1962) manual. Author’s Collection.

I seem to remember an Avalon Hill game where artillery had a 2 hex range; but I may well be mistaken.

Ever since the first computer wargames that I wrote back in the ’80s I have earnestly tried to make the simulations as accurate as possible by including every reasonable variable. With the General Staff Wargaming System we’ve added two new variables to ROI: 3D Line of Sight and an Accuracy curve.

Order of Battle for Antietam showing Hamilton’s battery being edited. Screen shot from the General Staff Army Editor. Click to enlarge.

In the above image we are editing a Confederate battery in Longstreet’s corps. Every unit can have a unique unit range and accuracy. You can select an accuracy curve from the drop-down menu or you can create a custom accuracy curve by clicking on the pencil (Edit) icon.

Window for editing the artillery accuracy curve. There are 100 points and you can set each one individually. This also supports a digitizing pen and drawing tablet. Screen shot from General Staff Army Editor. Click to enlarge.

In the above screen shot from the General Staff Wargaming System Army Editor the accuracy curve for this particular battery is being edited. There are 100 points that can be edited. As you move across the curve the accuracy at the range is displayed in the upper right hand corner. Note: every unit in the General Staff Wargaming System can have a unique accuracy curve as well as range and every other variable.

Screen shot showing the Range of Influence fields for a scenario from the 1882 American Kriegsspiel book. Click to enlarge.

In the above screen shot from the General Staff Sand Box (which is used to test AI and combat) we see the ROI for a rear guard scenario from the original American Kriegsspiel 1882. Notice that the southern-most Red Horse Artillery unit has a mostly unobstructed field of vision and you can clearly see how accuracy diminishes as range increases. Also, notice how the ROI for the one Blue Horse Artillery unit is restricted by the woods which obstructs its line of sight.

Screen shot of Antietam (dawn) showing Red and Blue ROI and battle lines. Click to enlarge.

In the above screen shot we see the situation at Antietam at dawn. Blue and Red units are rushing on to the field and establishing battle lines. Again, notice how terrain and elevation effects ROI. In the above screen shot Blue artillery’s ROI is restricted by the North Woods.

The above ROI maps (screen shots) were created by the General Staff Sand Box program to visually ‘debug’ the ROI (confirm that it’s working properly). We probably won’t include this feature in the actual General Staff Wargame unless users would like to see it added.

This is a topic that is very near and dear to my heart. Please feel free to contact me directly if you have any questions or comments.

How Will You Play General Staff?

Every wargame that I’ve designed allows the user to adjust important variables such as leadership and morale and how they affect combat. Usually included is the ability to design your own armies, maps and scenarios as well. However, with the General Staff Wargaming System we’ve added a new feature: the ability to control the realism level before playing a scenario.

The General Staff Wargame has two basic levels of play:

Simulation mode uses HQ units and a chain of command that passes orders down from the General HQ to the sub-commander to the individual unit. How fast the unit responds to the orders are affected by the distance that the courier must travel and the Leadership Value of the HQs.  Simulation mode also employs a more detailed combat resolution model and tracks the actual number of troops in every unit.

An example of Simulation Mode: the path (red line) and time (16 minutes) it will take for a courier to travel from JEB Stuart’s HQ to Munford’s cavalry with orders. Click to enlarge.

Kriegsspiel mode does not have HQ units and friendly units are moved directly and immediately (no transmission of orders via couriers). The combat resolution model is simpler and units have a value of 1-4 displayed by the number of unit icons on the map.

Antietam in Kriegsspiel mode. Notice that there are no HQ units (so no couriers to deliver orders) and units are represented by 1-4 icons. Units in column have a ‘tail’ that indicates the unit strength. Click to enlarge.

In addition to the two game modes (Simulation and Kriegsspiel) there are three Scenario Options:

Order of Battle (OOB) displayed / not displayed. Enemy units with known positions appear dark; enemy units ‘on the map’ but with unknown locations appear grayed out. This, of course, gives the user complete knowledge of the enemy’s OOB and, more importantly, knows when units from certain formations are not directly observable.

A mock up of how the Order of Battle option will appear (note this image was created from screen captures of the Scenario Editor and the Sand Box). Click to enlarge

Only friendly units directly observed by the General HQ are displayed. All other friendly units fade at their last known location. Couriers bring in unit location updates, but they are outdated by the time they arrive.

Only enemy units directly observed by the General HQ are displayed. All other enemy units fade at their last known location. Couriers bring in unit location updates, but they are outdated by the time they arrive.

If both of these above options are selected (only friendly and enemy units that are directly observable by your commanding General HQ) you will be simulating the Fog of War that field commanders of the age of gunpowder experienced.

What General George B. McClellan could actually see at Antietam. Screen shot (General Staff Sand Box). Click to enlarge.

We would like to hear from you and get your opinion on what realism features you will use in General Staff: