Showing posts with label attrition. Show all posts
Showing posts with label attrition. Show all posts

18 December 2010

Lanchester's Game

I've been kicking ideas around about using Lanchester's Laws as a way to create a point-value system (1) for balancing sides in a game, and one of these involves designing a game around this mathematical principle. Usually point system seem to evolve after the game is created; I want to create the point system first, and build a game to fit the math. I'm not sure this is possible, but it should be interesting to try. So I set out to write out the rules for a simple game to demonstrate the difference between Lanchester's Linear, Square, and Logarithmic (see footnote 2) Laws, which I will abbreviate with L1, L2L0. This turned out to be a really good idea, because it gave me an insight about how these laws arise, and a simpler way to explain them.

[A note aside: I wrote most of this post two months ago, and it gave me many good ideas for other post in the process, but I never quite figured out how to finish this one. Now I need this basic discussion to go along with some new posts I'm working on, so I'm making a second effort to finish this one.]

The Game
This game is really very simple, actually more of a thought experiment that explains Lanchester's laws.


Map, Movement, and Range: There is no map, and so no movement, and no range. This is an abstract game, and attacking another unit depend on which Attack Rule is being played (see below). It would be a more interesting game with these elements, but they only complicate the discussion. Maybe I will try to add these back in for another post. (Also good discussion points.)


Forces: Two sides, Blue and Red, each side have a number of tokens (B or R tokens, respectively) or markers representing the strength of each force (These might represent soldiers, tanks, etc.). Each player should start with 20 to 30 tokens, but not necessarily the same number.

Lethality: an attack is resolved by rolling a die: success kills one enemy, remove that marker/token. Assume equal lethality for simplicity, or allow to be different for completeness. Each attack has a lethality, or probability of a kill equal to b for Blue and r for Red. Lethality does not have to be the same for each side, but it simplifies this discussion if it is. For a good demonstration this should be a fairly small probability, so that the game will last 10-20 turns. The following discussion will assume a lethality of b = r = 1/6, so a roll of 1 on 1d6 can be used to resolve this easily.

Attacks: Every turn each player makes one or more attacks. The number of attacks a player makes depends on the Attack Rule in play, and could depend on the current size of each force (B or R).

Sequence of play:
1) Set up the game, decide force sizes, lethality, and Attack Rule.
2) Begin turn: players make one or more attacks, as determined by the Attack Rule in play.
3) Resolve attacks for each player based on the size of their force at the beginning of the turn.
4) Remove destroyed forces.
5) If both played still have forces remaining, go back to step 2 and play another turn. Play continues until one side is eliminated.

Attack Rules:

L1: Each player makes one attack every turn. No matter what casualties occur over the course of the game, each player will have same same total number of attacks, and this number will be proportional to the small of the two forces. This is exactly what is expected under the Linear Law.

L2: Each player makes one attack for every 5 tokens they have remaining (round up or carry fractions o the next turn). Over the course of the game the total number of attacks will be larger for the player with the larger initial force. The ratio of total Blue attacks to Red attacks will be proportional to (B/R)^2 [the ratio B/R, quantity squared]. (It does not have to one attack for every 5 tokens, it only need be some small proportion of the current size of the force. 5 was just convenient).

L0: Each player makes one attack for every 5 (convenience again) of the other sides tokens. Here the number of attacks made against you is proportional to the size of your own force (see footnote 2 again). This seems like a strange rule, but war in unhealthy! Putting your army in the field makes if subject to direct and indirect threats. Starvation, disease, accidents, mules kicks, artillery and bombing, are all hazards that put the entire force at risk. Sometimes the more you bring, the more you lose.

Discussion:
Each of these "attack rules" will lead to distinctly different outcomes for the game. More importantly, a form of one or more of these rules is inherently present in all war games and combat simulations. Even if it is not written explicitly, but it will still arise from how the game plays.
Game combine these rules in interesting ways. For instance, terrain, stacking rules, and range limits will tend to restrict some units in a game to the L1 attack rule. Other units will have a clear field of fire to attack (and be attacked) will use the L2 rule. Some units might stay in relative safety and threaten the other force from afar (like artillery) and subject the other side to the L0 rule. A unit firing from a bunker might only be attacked under the L1 rule, may be able to attack other using the L2 rule. so it's not necessarily the same rule in effect for both sides.

I have read many papers trying to model data from historical battles as if there is a new rule that somehow combines two or more of these rules. From a certain standpoint that is the wrong approach. These rules might mix, affecting different parts of armies in different ways, but there is no rule that says you will always get the same sort of mixture every time. In fact, you will almost certainly get a little different mixture in every battle. Lanchester's laws are not something over which either side has total control - they are something that happen to you during the battle. In a close fight, the army that is better able to exploit the rules is more likely to win.


Footnotes:
(1) Such as BattleValue in Battletech, which is the one I know the best. Ogre/GEV has a very simple point system. Warhammer 20K+/-20K has a point system but I know nothing about it other than it exists. If you can suggest other games that use point systems please post or email me about it so I can look into this topic further.
(2) The "Logarithmic" law arose from attempts to fit actual data of battle casualties to either the Square or Linear law, and finding that sometimes neither one is a very good fit. I have avoided mentioning it thus far in order to simplify discussion. The interpretation of the Logarithmic Law implies that the casualties suffered by one force are proportional to the size of one own force (not the opposing force). This seems unusual, but is sometimes observed in historical data describing large scale battles. See Fricken (1997) for the an excellent discussion and justification for the Logarithmic law.
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29 November 2010

Gratuitous Space Battles

This is actually part 3 of my series on Lanchester's Laws, sort of. Since writing parts 1 and 2 have been reconsidering the whole topic, and I seem to have a number of ideas that branch off of this topic but one doesn't necessarily follow another. Therefore I've decided to worry a little less about how this all fits together, and just write something and get it posted. The figuring out can come later.
That said, it time for something I've been putting off for far too long ...

... which is a game called Gratuitous Space Battles. GSB is my first computer game purchase in several years, and I consider it money well spent. Let's start with a video of the action!



This operates a little differently from most space battle games; this is a Tower Defense game. If a game is a series of interesting decisions, then all the decisions in this game come at the beginning. First you design ships, choose your fleet, give then orders, and click on START. Then you sit back and WATCH the battle unfold. If you lose the battle, you go back and try a different set-up. if you WIN the battle, you can go back and try to win with few resources. The replay value of this game is very high.

Gratuitous Space Battles has been called "massively single player", because you can submit and download scenario challenges from other players in the online GSB community. I haven't done much of this yet, but my experience so far has been very positive, with other players happily responding to my challenges, politely pounding me to newbie-snot, and offering tips on how I might do better. This offers the sort of difficulty level you can only get from human players, even though you aren't playing online, or even simultaneously.
GSB has a downloadable Demo that I would like you to try. This isn't just because I think it is a cool game; which it is, but I have something specific in mind. GSB is a perfect way to demonstrate Lanchester's Square Law in action. If you want to give this a try, download the demo and play a few rounds to get the idea how it works. Once you have that under you belt, try the following setup:

Create a fleet with as many fighters as you can manage, and tune it until it wins consistently. Next, start removing fighters a few at time until your fleet no longer wins easily. Lanchester's Square Law predicts that the casualties you will inflict are proportional to the square of the ratio of friendly/enemy units. With a bit of experimentation you should be able to find the balance point - the point where your fleet doesn't always win, but the addition or subtraction of just a few fighters changes the balance drastically. Try to find the point where adding 2-3 fighter practically guarantees a win, but subtracting 2-3 fighters is a sure loss. In GSB, fighters are as close to single soldiers as you can get, and it is interesting to find that balance point where "just a few men" can completely turn the tide of the battle.

Some hints if you want them, in white text in case you prefer to figure things out for yourself. Select the text below to view:
[hidden text]
Choose a few cruisers with 2-3 Plasma Launchers, and a few shorter range weapons.
One cruiser should have a Fighter Support Bay, and order your fighters to be "Cautious" so they will will return to the bay for repairs.
Faster, lightly-armed fighters attacking at minimum range (inside cruiser shields) are much more effective than slow, heavily armed fighters.
Give your fighters orders for "Cooperative", "Vulture", and "Stick Together". You should also order them to "Escort" one of your cruisers (at range 600) so they do not wander too far from the rest of your fleet.

[/hidden text]


OK, now for just a tiny bit of mathematical consideration. Suppose we take the source code for GSB and simplify it - stripping out everything that makes it look like a game, removing all options except for how many ship there are and the firepower of each ship, removing movement (assuming every ship can fire at any other), leaving just the input of forces at the beginning and a report of the battle outcome. What we have left is a basic attrition model; a simple program that conducts a simulated "battle", even though we don't get to watch the progress of that battle any more. With all the simplifications it is barely resemble a game, but it become a very effective tool for studying the effect small changes in force selection (or force orders) can have on the outcome of a battle. Consider putting this tool inside of a computer program and run through hundred, thousands, or even millions of scenarios, each with slightly different starting conditions, then look at which starting conditions lead to success or failure.

Just like my suggested example above, tinkering with the number of fighters to find a balance point, you might tinker with the behavior of forces. You can examine things like the effect of the priority in which enemy units are attacked, maybe add ammunition considerations, command and control, whatever you like. The point is, there can be value in studying very basic considerations in a model that has been stripped of all but the most basic structure. It's true that the effect of something complex (like command and control) probably depends on any number of other factors, but if you don't understand how something works in a simple model, then it is unlikely you can understand how it works in a more complex model.


I'm a big fan of simplifying thing down to base elements, and trying to understand them from the bottom up. Gratuitous Space Battles, even in demo form, is a good tools for studying Lanchester's Laws. It's not an ideal tool for such - that would require your own program - but it is very accessible to anyone with an interest in the topics, and it's a heap of fun too.  I give GSB a four-robot rating :-)
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Over at the developer's blog, you can read about The Fighter Spam Issue he is having with the GSB campaign game. Essentially, by taking advantage of Lanchester's Squared Law, it becomes fairly simple to construct a fighter-heavy fleet that is nearly unbeatable. Balancing the game requires in this situation require putting some limits on the usefulness or availability of fighters.

Credits: Some of the images here are taken from the GSB developer's site, or the GSB Facebook page, and the rest are screenshot I created.

A question in the comments below inspired this response and example, and this related post.
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09 July 2010

Lanchester's Laws and Attrition Modeling, Part II

In Part One I introduced the basic concept behind Lanchester's Laws, and now I want to write more about how this applies to games. This time I'll start off with Ernest Adams' excellent 2004 Gamasutra article, and follow up with my take on actually applying this to a game.


[Alternate Link to Ernest Adams article, in case the Gamasutra link flakes out again.]

Adams makes a particular good point about Lanchester's Laws and "victory".

Now, Lanchester's Laws are far from perfect. For one thing, they only apply to battles of attrition, in which the object is to wipe out the other side. If "winning" a battle is defined in some other way -- and modern Western militaries don't normally consider slaughtering every last opponent to be a legitimate objective -- then Lanchester's Law has nothing to say about who wins. Napoleon "won" every battle he fought in his march into Russia, but he still lost 98 percent of his men and was forced to retreat without achieving his objective.

On the other hand, some wargames are often fought to the last man standing, so if you are trying to understand game balance it is well worth considering. Some early comments tell me that rest of this post may be a confusing slog through a lot of math - I'm afraid that is the nature of the beast. All I can do is ask the reader to bear with me for now, and stay tuned for Part III where there will be some more accessible examples. I will start of again by stating my assumptions, fixing some errors I made last time.

This is a very simplified model of combat; Each side has identical soldiers; Each side has a fixed strength which governs the proportion of enemy soldiers killed. Range, terrain, movement, and all other factors that might influence the fight are either abstracted to the proportion killed or ignored entirely. In the derivation from differential equations casualties are inflicted continuously over time, but it also works to think of casualties inflicted in rounds or turns, which will be a more familiar setting to most gamers.

My first error last time was stating this in terms of the probability of killing an enemy soldier instead of a proportion or kill-rate. The differential equation derivation of Lanchester's Laws is a deterministic relationship that does not involve probabilities at all. I'm a statistician and tend to think in terms of probabilities rather than fixed proportions, and I'm also working my way up to demonstrating a probabilistic derivation of the same thing, so forgive me if I got a bit ahead of myself. A definition involving probabilities should be even more useful because it will demonstrate the degree of uncertainty involved in a balanced game.

My second error was in describing the total casualties for the winning side in my example. Side 2 loses all 2000 soldiers, and side 1 suffers casualties equal to 4/9ths (44%) of 2000 soldiers, for a total of 889. I had incorrectly stated that side 1 would lose 4/9ths of its total force (which would be 1400 soldiers), and the previous post has been corrected.

Notes on some abbreviations I may use (some changes since part one):
  • Pk = "Proportion killed" or combat effectiveness, with subscript k1 or k2 if it matters. This is usually a small proportion. 
  • RPk1/Pk2 , the ratio of combat effectiveness. (1/R = Pk2/Pk1)
  • N1N2 = The initial force sizes (before combat) of each side.
  • n1, n2 = The remaining force sizes at the end of combat.
  • C1C2 = The total casualties suffered by each side at the end of combat (C1 = N1 - n1).
  • a = Exponent on the force size. For the Linear Law a=1, and for the Squared Law a=2.
  • "~=" is used to represent "approximately equal to".
  • Be aware that the !@#@!#%&*#!!! Blogger editor is subverting every effort to use smaller fonts as subscripts in the text. Hopefully the subscripts will be clear from context.
Here is a an expanded version of the formula from part one. That formula only worked in a special case; this is more general:
[Edit: The k1 and k2 subscripts are reversed, dangit.]

This is a more general form that accounts for both the Linear and Square Laws, adds the relative combat effectiveness Pk's, and allows for situation in between with 1<a<2. This assumes the condition of combat and acquiring targets are the same for both sides, and so the value of a is the same for both. (Yes it can be different, but that really complicates things). I should also clarify that in a battle to the last man standing, where either C1 = N1 or C2 = N2, or equivalently n1 = 0 or n2 = 0 (one side is completely destroyed).

If a game is perfectly balanced then both sides should be destroyed at the same time, which results in both n1 = 0 and n2 = 0. Plugging these in and a bit of algebra gives:
Some important points:
  1. THE important point of Lanchester's Laws, is that the exponent representing the advantage of a higher rate of target acquisition applies to the size of the force (N), but not to the fighting effectiveness of the force (Pk). Under the Squared Law, any advantage that army 1 might have in combat effectiveness is usually quickly overcome if army 2 has the larger force. 
  2. Lanchester's Laws are not a governing rule of combat, they are a description of an ideal principle. In actual combat/play this ideal is unlikely to hold. If one player has a range advantage (tending towards a=2), other other will make use of terrain to counter this (tending towards a=1). Battles tend to occur in sets of smaller skirmishes, each with it's own circumstances, and the final result may represent some average of these skirmishes. 
  3. There is a third variation on Lanchester's Laws, known as the logarithmic law, which has relevance to interpreting historical data, but that will have to be a topic for another day.

So how is this used to balance a game? Let's suppose we have a hypothetical game where combat can potentially operate under the Squared law, but due to range and movement limitations effectively operates somewhere between Linear and Squared. I'll use a=1.5 to represent the actual state of this game, and work out examples under three cases:

Example 1 (Balance relative effectiveness):
  1. For the Linear Law a=1.0, N1 = 3000, N2 = 2000, Pk1 = 0.01, and solving for Pk2 gives Pk2 = 0.015 and R = 0.67 (or 1/R = 1.5).
  2. For the Squared Law a=2.0, N1 = 3000, N2 = 2000, Pk1 = 0.01, and solving for Pk2 gives Pk2 = 0.0225 and R = 0.444  (or 1/R = 4/9 = 2.25).
  3. For my in-between value of a=1.5, and again N1 = 3000, N2 = 2000, Pk1 = 0.01, and solving for Pk2 gives Pk2 = 0.018371 and R ~= 0.554 (or 1/R ~= 1.84).
If I want to balance a scenario with these forces (or any 3:2 force ratio) side 2's forces will need to be between about 1.84 times as effective as side 1's in order for this to be a fair fight. What actually happens in the game will still depend on chance and the ability of players to take advantage of opportunities during play, but that's the hypothetical balance point.

Example 2 (Balance force sizes):
  1. For the Linear Law a=0.01, N1 = 3000, Pk1 = 0.01, Pk2 = 0.015 and solving for N2 gives N2 = 2000.
  2. For the Square Law a=2.0, N1 = 3000, Pk1 = 0.01, Pk2 = 0.015 and solving for N2 gives N2 ~= 2450.
  3. For the in-between a=1.5, N1 = 3000, Pk1 = 0.01, Pk2 = 0.015 and solving N2 for gives N2 ~= 2289.
If I want a balanced scenario where the sides have this relative effectiveness (2:3 ratio, R = 0.67) side 2 will need an initial force size of about 2450 2289 to balance with side 1 in a fair fight. The outcome still depends on what happens in the game, but that's the hypothetical balance point.

Note that I arbitrarily chose a=1.5 for this example, pretending that I have a game where this is true. In practice I don't think it is possible to design a game to a particular value of a. What you can do is assume a value for a and design a game around it, assigning values and balancing scenarios with different types of units in this manner. This is difficult though, because in a game with many different types of units there is potentially a different balance point for every pair of units that might face each other, and there isn't any simple formula that can solve it for for us. This process gets VERY complicated.

At this point I have probably created more questions than I have answered. That is a problem, but I need to stop somewhere. The next part will hopefully include some more accessible examples, and some toy spreadsheets you can download to play with.
In my research I found two recent papers by Perry that were very helpful (especially 6 below) and greatly improved my own understanding of the topic. The MacKay paper (4) is maybe a simpler article to read first. You don't necessarily need to understand differential equations to read these, but it helps.

Part III of this series is here.

Bonus Link!



Lanchester Systems and the Lanchester Laws of Combat
by "The Custodian" at everything2.com
This is another basic introduction to Lanchester's Laws. The author (semi-anonymous) spends more time on the differential equations and some practical aspects that I glossed over completely, so it might be worth your time.

References and Reading (updated since part one)
  1. Ernest Adams, "Kicking Butt By the Numbers: Lanchester's Laws", a Designer's Notebook, Gamasutra webzine, August 4, 2004.
  2. Bruce Fowler, De Physica Belli: An Introduction to Lanchestrial Attrition Mechanics Part One, Defense Modeling Simulation and Tactical Technology Information Analysis Center, Huntsville, AL, 1995.  [Early versions of this series can be found online at DTIC: 1,2,3.]
  3. Michael J. Artelli and Richard F. Deckro, The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 2008 5: 1-20
  4. Niall MacKay, Lanchester combat modelsarXiv:math/0606300v1 [math.HO] (2006)
  5. Wikipedia contributors. "Lanchester's laws." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 3 May. 2010. Web. 23 Jun. 2010.
  6. Perry, Nigel. Defence Science and Technology Organisation (Australia). Joint Operations Division 2009 Fractal effects in Lanchester Models of Combat [electronic resource] / Nigel Perry Defence Science and Technology Organisation, Canberra.
  7. Perry, Nigel. Defence Science and Technology Organisation (Australia). Defence Science and Technology Organisation (Australia). Defence Systems Analysis Division. 2006 Verification and validation of the fractal attrition equation [electronic resource] / Nigel Perry DSTO, Edinburgh, S. Aust.
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27 June 2010

Lanchester's Laws and Attrition Modeling, Part I

Consider of problem of two armies facing each other of a field of battle. One army is larger, but the other army is better armed. Once battle is joined, the two sides wear each other down until one is completely destroyed, or more likely, until one has suffered so many casualties it can no longer hold the field, and so retreats in defeat. There is a mathematical way to describe this sort of battle, a battle of attrition, and it is a topic I've been wanting to introduce here since I first started. I hesitated though, because it's a difficult topic with few really satisfying answers. Rather that reinvent the wheel, I'm going to link to a source articles and add comments of my own. This should easily make a series, maybe a long series if I don't get tired of it first.

So let's get things started - this first link is good introduction to the topic. After you get back, I'll repeat the definition in my own words, and explain where the Wiki article, and most articles on this topic, get it wrong.

Wikipedia - Lanchester's Laws
[edit April 2010: Of course Wikipedia changes sometimes! The article linked above is still good, but I have quoted the relevant proportion of the classical interpretations here.]

Lanchester's Linear LawIn ancient combat, between phalanxes of men with spears, say, one man could only ever fight exactly one other man at a time. If each man kills, and is killed by, exactly one other, then the number of men remaining at the end of the battle is simply the difference between the larger army and the smaller, assuming identical weapons.[...]Lanchester's Square LawWith firearms engaging each other directly with aimed fire from a distance, they can attack multiple targets and can receive fire from multiple directions. The rate of attrition now depends only on the number of weapons firing. Lanchester determined that the power of such a force is proportional not to the number of units it has, but to the square of the number of units. (reference 6 below).

My turn. This is a very simplified model of combat; Each side has identical soldiers; Each soldier has an identical probability of killing a soldier on the other side, if they can (the probability does not have to be the same for both sides). Range, terrain, movement, and all other factors that might influence the fight are either abstracted to the probability of a kill or ignored entirely. In the derivation from differential equations casualties are inflicted continuously over time, but it also works to think of casualties inflicted in rounds or turns, which will be a more familiar setting to most gamers.

Note on some abbreviations I may use:
Pk = "Probability Rate of a kill", with subscript k1 or k2 if it matters. This should be a small value relative to the size of the force and time interval. [Correction: There is no probability involved here. This should be the proportion or rate of casualties that results from combat over a short length of time.]
N1, N2 = The initial force sizes (before combat) of each side.
C1, C2 = The total casualties suffered by each side at the end of combat.


The Linear Law applies when one soldier can only fight one other soldier at a time. If one side has more soldiers, some of them won't be fighting all the time as the wait for an opportunity to attack. In this setting, the casualties suffered by both sides are proportional to the number actually fighting (and the relative probability of a kill). If the Pk is the same for both sides, then both sides will suffer casualties equaly to the size of the smaller force. This was originally called Lancherster's Law of Ancient Warfare, because it tries to model what happens if neither side has ranged weapons, and so are fighting with swords or spears (but it works equally well with ba'tleth or light-sabers).

The Squared Law, sometimes known as Lanchester's Law of Modern Warfare, is intended to apply to ranged combat, and it quantifies the value of the relative advantage of having a larger army. With the Linear Law, this advantage is proportional to the size of the forces, but when the entire force of both sides can engage the other simultaneously, the relative advantage is a function of the square of the force size. Again assuming equal Pk, the casualties of the larger army will be proportional to the ratio of the squared forces sizes.
So for example, if N1 = 3000 and N2 = 2000, then this ratio C2/C1 is equal to (dropping zeros, 3^2 / 2^2 = ) 9/4 or 2.25. By the end of the battle side-2 will have suffered 2.25 casualties to every 1.0 on side-1. Conversely, side-1 will lose 4/9 or 44.4% of side-2's loses, for total casualties of (4/9)*2000 = 889 soldiers.

Now for the bug. There is nothing wrong with the mathematical derivation, but there is considerable confusion about the interpretation. That the Squared Law describes the advantage of superior numbers in ranged combat is the practical interpretation, but range is not even considered in the derivation. The Squared Law really has nothing to do with range - what really matters is the rate of acquiring new targets. Having ranged weapons generally let's your soldiers acquire new targets as fast as they can shoot, whereas with a spear or sword (Linear Law) you have to locate a target and then move to engage them. In real life this may be a trivial distinction, because the "advantage of range" interpretation makes sense in most situations. However, games offer some alternatives where the Squared Law applies, but it clearly has nothing to do with range. Some examples of the Linear and Squared Laws in action, both on the gaming table and in real life:

  1. For a platoon of Battle-axe wielding Dwarven warriors the Linear Law would generally apply, but make that a platoon of motorcycle mounted Battle-axe wielding Dwarven warriors that can move to engage any target on the gaming table, and suddenly the rate of target acquisition is as high as that of unit with ranged capability, and so the Squared Law applies.
  2. (For the Battletech players) Consider a Battlemech like the Dasher H that carries powerful but short range weapons. This would usually imply the Linear Law. The limitation of short range weapons is irrelevant here because it moves so fast it can effectively engage most targets immediately.
  3. In a game where some units may be effective invisible, either through stealth technology, "cloaking", or magical invisibility, then the advantage of range for acquiring targets may be effectively nullified, and the Linear Law will prevail in the battle.
  4. The US military is increasingly making use of battlefield information systems to give field commanders knowledge of where the enemy is - to allow them to acquire targets first, and in the most advantageous way possible. This gives the advantage of the Squared Law to the US military, where the opposition with limited information is effectively fighting under the Linear Law.
  5. Guerrilla warfare, in setting such as Iraq and Afghanistan, it is much easier for insurgent to find US targets than is it for the US to find insurgent targets, and the Square Law applies.

And here is the take-home lesson: Lanchester's Laws are NOT about range. Range doesn't matter, "ancient" or "modern" doesn't matter - It's all about the rate of target acquisition. It's OK to think about range being the key concept in most settings, because that is the mechanism which allows new targets to be attacked immediately. However, if you want to apply Lanchester's Laws when designing a game, or in understanding how game balance works, this distinction may be important.

There is more, much more, which is why I'm spliting this up into a series of posts. I have some references below, some of which didn't even get mentioned here, so if you don't want to wait for me you could peek ahead at some upcoming topics. Finally, here are some closing notes that didn't make it into the text above:

  1. Though Lanchester generally gets the credit, a Russian mathematician named Osipov also wrote on the same topic at about the same time.
  2. In application of Lanchester's Laws to historical data, it is generally found that some mix of the Linear and Squared Laws is the rule, not one or the other exclusively. I don't have any references on this below yet, but a Google search on Lanchester and Helmbold ought to turn up something relevant.
  3. This has implications on point systems for balancing game scenarios, such as Battle Value in Battletech. Such point systems tend to have serious flaws, and Lancherster's Laws illustrate why: no single point system can be correct in every setting.
  4. I implied, but did not state, that it is possible for one side/army to be operating under the Linear Law and the other under the Squared Law. This may be a topic in coming posts.
  5. The assumptions for Lanchester's Laws are rarely true in a game setting, much less in reality. However, they do demonstrate the superiority of numbers principle in combat, which is a very important lesson, even if somewhat obvious.


References and Reading
(Please pardon the hodgepodge of styles. Organizing my math & gaming references is an ongoing project.)


  1. Ernest Adams, "Kicking Butt By the Numbers: Lanchester's Laws", a Designer's Notebook, Gamasutra webzine, August 4, 2004.
  2. Bruce Fowler, De Physica Belli: An Introduction to Lanchestrial Attrition Mechanics Part One, DEFENSE MODELING SIMULATION AND TACTICAL TECHNOLOGY INFORMATION ANALYSIS CENTE R HUNTSVILLE AL, 1995. [Early versions of this series can be found online at DTIC: 1,2,3.]
  3. Michael J. Artelli and Richard F. Deckro, The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 2008 5: 1-20
  4. Niall MacKay, Lanchester combat models, arXiv:math/0606300v1 [math.HO] (2006)
  5. Wikipedia contributors. "Lanchester's laws." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 3 May. 2010. Web. 23 Jun. 2010.
  6. Wikipedia contributors. Lanchester's laws. (2011, March 30). In Wikipedia, The Free Encyclopedia. Retrieved 00:19, April 3, 2011.
Update: Part II is up.

Epilogue: I'm getting a lot of hits via Facebook, maybe thru Networked Blogs, or possibly posted on a group somewhere. If you came to this page via Facebook, please leave me a comment about how you got here. --- Thanks --- Dan

1/24/2024: I just found this article on Lanchesters Laws and applying them to plan encounters for Dungeons & Dragons. Go read it! 
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