Game Probability: Risk Rules & Closed-Form Solution

In summary, the probability of capturing a territory and the expected number of armies lost by the attacker can be calculated using the given expressions, taking into account the number of attacking and defending armies.
  • #1
Big-Daddy
343
1
In a game of Risk, the rules are:

The rules for determining how many dice a player may roll:

1. The attacker may roll as many dice as the number of attacking pieces he is using, to a maximum of 3. If A>3, the attacker continues to roll 3 dice per turn.
2. The defender may roll as many dice as the number of armies on his country, to a maximum of 2. If D>2, the defender continues to roll 2 dice per turn.

The rules for deciding the outcome of a particular throw of the dice are as follows:

1. The highest attacker die is compared against the highest defender die. Whoever has the lower number loses one army. Ties go to the defender.
2. The procedure is repeated for the second-highest dice, where both attackers and defenders have a second die.

If you attack a territory defended by D armies with A armies, what is the probability that you will capture this territory? In such a scenario, how many armies should you expect to lose (whichever side that will prevail)?

Previously I had thought we needed a recursive solution, and reached one with the help of some members on this forum. But now I wonder if a closed-form solution is possible. Take a look at this report: http://web.archive.org/web/20060919204627/http://www4.stat.ncsu.edu/~jaosborn/research/RISK.pdf. As noted on page 2, A is the number of attacking armies and D is the number of defending armies.

First of all, the probabilities of each outcome on a certain turn are given on page 5. These are in exact form. We don't need to worry about how they were obtained, we can just use them as they are now. What really interests us is the section entitled "The Probability of Winning a Battle", and what comes after that (pages 4 onwards).

How do we express the function f(n)ij, found at the bottom of page 4, in closed form, in terms of the values of n, i and j? If we can figure this out, then, as noted half-way down page 5, fij is simply the sum of f(n)ij from n=1 to n=∞. And then, at the bottom of page 5, we perform a summation across all values of j. i=A*D apparently, or perhaps I am interpreting that wrong; it seems strange that a transition probability will be the same for the 4v5 case as for the 10v2 case.

Anyway, if someone can give me help on how to reach the final 2 expressions on the bottom of page 5 in closed-form, in terms of A, D and the dummy variables, that would be a great start.
 
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  • #2
Assuming you are familiar with the concept of probability and combinatorics, the probability of capturing a territory with A armies attacking and D armies defending is given by the following expression: P(capture) = 1 - (A/D)*(1 - (A-1)/D)*(1 - (A-2)/D)^2... The expected number of armies lost by the attacker is given by the following expression: E(armies lost by attacker) = A*(1 - (A-1)/D)*(1 - (A-2)/D)^2... Note that both of these expressions assume that A is less than or equal to D. If A is greater than D, then the attacker will always win and the expected armies lost by the attacker is just A.
 

What is game probability?

Game probability is the likelihood of a certain outcome or result occurring in a game. It takes into account various factors such as player skill, luck, and strategy to determine the chances of one player winning over another.

What are risk rules in a game?

Risk rules refer to the specific guidelines and regulations that govern a game. These rules dictate how the game is played, what actions are allowed, and what consequences occur as a result of certain moves. They are important in maintaining fairness and balance in a game.

What is a closed-form solution in gaming?

A closed-form solution is a mathematical equation or formula that can be used to accurately predict the outcome of a game. This solution is based on a set of rules and assumptions, and can help players strategize and make informed decisions during gameplay.

How can game probability be calculated?

Game probability can be calculated using various methods such as probability theory, statistical analysis, and simulations. These methods take into account different variables and factors to estimate the likelihood of a particular outcome in a game.

Why is understanding game probability important?

Understanding game probability is important because it can help players make better decisions and improve their chances of winning. It also allows for more strategic gameplay and a deeper understanding of the game mechanics. In addition, it can also be used to design and balance games to ensure fair and enjoyable gameplay for all players.

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