diff --git a/ipynb/risk.ipynb b/ipynb/risk.ipynb index 98f8871..575d9f7 100644 --- a/ipynb/risk.ipynb +++ b/ipynb/risk.ipynb @@ -197,7 +197,7 @@ { "data": { "text/plain": [ - "[3, 3, 6]" + "([5, 5, 4], [5, 1], (1, 1))" ] }, "execution_count": 8, @@ -206,7 +206,10 @@ } ], "source": [ - "random_roll(3) # Example roll" + "# Example battle\n", + "A_dice = random_roll(3)\n", + "D_dice = random_roll(2)\n", + "A_dice, D_dice, battle_deaths(A_dice, D_dice)" ] }, { @@ -256,7 +259,7 @@ { "data": { "text/plain": [ - "(9,)" + "(11,)" ] }, "execution_count": 10, @@ -272,7 +275,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "That final state says that the attackers won—there are 9 attackers and no defenders left. \n", + "That final state says that the attackers won—there are 11 attackers and no defenders left. \n", "\n", "# Predicting the Unfinished Game: Estimating Probabilities\n", "\n", @@ -354,15 +357,14 @@ { "data": { "text/plain": [ - "ProbDist({(4,): 0.1,\n", - " (15,): 0.1,\n", - " (20,): 0.1,\n", - " (1, 1, 5, 1): 0.1,\n", - " (16,): 0.2,\n", + "ProbDist({(5,): 0.2,\n", + " (8,): 0.2,\n", + " (22,): 0.1,\n", + " (21,): 0.1,\n", " (11,): 0.1,\n", - " (6,): 0.1,\n", - " (12,): 0.1,\n", - " (8,): 0.1})" + " (0, 5, 1): 0.1,\n", + " (13,): 0.1,\n", + " (1, 1, 1): 0.1})" ] }, "execution_count": 14, @@ -400,7 +402,7 @@ { "data": { "text/plain": [ - "0.7960000000000003" + "0.8190000000000004" ] }, "execution_count": 16, @@ -427,7 +429,7 @@ { "data": { "text/plain": [ - "0.8300000000000003" + "0.8130000000000003" ] }, "execution_count": 17, @@ -458,11 +460,11 @@ "\n", "In deciding whether to use the exact calculation approach, there are three considerations:\n", "\n", - "- **Is it worth the effort?** If I only wanted to know whether the attackers chance of winning is more or less than 50%, then the Monte Carlo approach is the simplest way to answer the question. The code will be simple and straightforward. If I need 0.0001% precision on the win probability, then exact calculation is called for.\n", + "- **Is it worth the effort?** If I only wanted to know whether the attackers chance of winning is more or less than 50%, then the Monte Carlo approach is the quickest way to answer the question. The code will be simple and straightforward. If I need 0.0001% precision on the win probability, then exact calculation is called for.\n", "- **Is it possible?** The exact calculation approach only works for **finite games**. \n", "- **Is it feasible?** Computation may take too long if there are too many possible states of the game.\n", "\n", - "**Worth the effort?** In general, the code for an exact calculation is more complex than for a Monte Carlo simulation, and thus it will take more time to write the code, and there will be more opportunity for bugs to sneak in. Monte Carlo code deals with the single current state of the simulation, for example: \n", + "**Worth the effort?** In general, the code for an exact calculation is more complex than for a Monte Carlo simulation, and thus it will take more time to write and debug the code. Monte Carlo code deals with the single current state of the simulation, for example: \n", "\n", " while not terminal(state):\n", " \n", @@ -470,13 +472,13 @@ "\n", " while any(not terminal(state) for state in probdist):\n", " \n", - "Adding all these loops to the code makes it more complex.\n", + "Adding all these loops to the code makes it more complex. After the shared basics of representing states and battle outcomes, we need just just 10 non-comment lines of code to implement the Monte Carlo method (in `simulate_campaign`, `monte_carlo`, and `random_roll`), but 22 lines to implement exact calculation (in `campaign_probdist`, `battle_deaths_probdist`, `battle_update_probdist`, and `all_rolls`).\n", "\n", - "**Possible?** Imagine a *Risk* rule change where if the attackers roll three 6s and the defneders roll two 6s, then both sides *gain* an army. For the Monte Carlo simulation it would be trivial to add a single `if` statement to handle this rule, and the expected run time of the program would hardly change. But with the exact calculation everything has changed, because we now have an **infinite** game, where there will always be some possible state that has not terminated. (To deal with these we would have to make some compromises, such as stopping the calculation when there are still some nonterminal states, as long as they have very low probability.)\n", + "**Possible?** Imagine a *Risk* rule change where if the attackers roll three 6s and the defneders roll two 6s, then both sides *gain* an army. For the Monte Carlo simulation it would be trivial to add a single `if` statement to handle this rule, and the expected run time of the program would hardly change. But with the exact calculation everything has changed, because we now have an **infinite** game: no matter how far ahead we look, there will always be some possible states that have not terminated. (To deal with these we would have to make some compromises, such as stopping the calculation when there are still some nonterminal states, as long as they have very low probability in total.)\n", "\n", - "**Feasible?** Imagine that before each battle, every army independently has the option to take one of ten possible actions (e.g. to move to a safe neighboring territory). Then with 100 armies, the very first move has $10^{100}$ outcomes, meaning that the probability distribution requires more states than the number of atoms in the universe. (To deal with this we would either stick with the Monte Carlo simulation, or a varioant of it such as [particle filtering](https://en.wikipedia.org/wiki/Particle_filter) in which we maintain a **sample** of several possible states–more than a single state, but less than the complete state distribution.)\n", + "**Feasible?** Imagine a rule change where before each battle, every army independently has the option to take one of ten possible actions (e.g. to move to a safe neighboring territory). Then with 100 armies, the very first move has $10^{100}$ outcomes, meaning that the probability distribution requires more states than the number of atoms in the universe. (To deal with this we would either stick with the Monte Carlo simulation, or a variant of it such as [particle filtering](https://en.wikipedia.org/wiki/Particle_filter) in which we maintain a **sample** of several possible states–more than a single state, but less than the complete state distribution.)\n", "\n", - " The *Risk* campaign problem as it stands leads to a very efficient exact probability calculation (possible, feasible, and worth it, IMHO). If there are $n$ total armies to start, then there are fewer than $n^2$ possible states, and the game can last no more than $n$ moves. With $n$ in the range of a few hundred, computation takes less than a second; much faster and more accurate than doing 100,000 simulations." + " The *Risk* campaign problem as it stands leads to a very efficient exact probability calculation (possible, feasible, and, IMHO, worth it). If there are $n$ total armies to start, then there are fewer than $n^2$ possible states, and the game can last no more than $n$ moves. With $n$ in the range of a few hundred, computation takes less than a second; much faster and more accurate than doing 100,000 simulations." ] }, { @@ -487,7 +489,7 @@ "\n", "The function `battle_deaths` was defined above to return the specific death counts for a specific dice roll. \n", "\n", - "Now we'll define `battle_deaths_probdist` to give a probability distribution over all possible battle outcomes, corresponding to all possible dice rolls. The input to `battle_deaths_probdist` is a state giving the number of attacking and defending armies for just this one battle (not the total number of attacking and defending armies). Thus, the attackers will always be 3, 2, or 1, and the defenders will always be 2 or 1. I define it this way, rather than passing in the full state of the campaign, so that I can **cache** the results and reuse them in subsequent battles, for efficiency." + "Now we'll define `battle_deaths_probdist` to give a probability distribution over all possible battle outcomes, corresponding to all possible dice rolls. The input to `battle_deaths_probdist` is a state giving the number of attacking and defending armies for just this one battle (*not* the total number of attacking and defending armies in the current state). Thus, the attackers will always be 3, 2, or 1, and the defenders will always be 2 or 1. I define it this way so that I can **cache** the results and reuse them in subsequent battles, for efficiency." ] }, { @@ -498,12 +500,13 @@ "source": [ "@lru_cache()\n", "def battle_deaths_probdist(state) -> ProbDist:\n", - " \"\"\"A probability distribution of deaths in a battle.\"\"\"\n", + " \"\"\"A probability distribution of deaths in a battle.\n", + " State is (A, D) where 1 <= A <= 3 and 1 <= D <= 2.\"\"\"\n", " return ProbDist(battle_deaths(A_dice, D_dice)\n", - " for A_dice in rolls(A(state))\n", - " for D_dice in rolls(D(state)))\n", + " for A_dice in all_rolls(A(state))\n", + " for D_dice in all_rolls(D(state)))\n", "\n", - "def rolls(n) -> Iterable[Dice]: \n", + "def all_rolls(n) -> Iterable[Dice]: \n", " \"\"\"All possible rolls of `n` dice.\"\"\"\n", " return itertools.product(die, repeat=n)" ] @@ -536,9 +539,9 @@ "source": [ "# Exact Probability Distribution over a Campaign\n", "\n", - "The function `campaign_probdist` mimics `campaign`, except that the former updates a `ProbDist` whereas the later updates a `State`. We start with certainty: there is a 100% chance that we are initially in the `start` state. But the [fog of war](https://en.wikipedia.org/wiki/Fog_of_war) means that uncertainty arises: we don't know how the dice will land, so we don't know the outcome of the very first battle. Subsequent battles add more uncertainty. \n", + "Our old function `campaign` is mimiced by `campaign_probdist`, except that the former updates a `State` whereas the later updates a `ProbDist`. We start with certainty: there is a 100% chance that we are initially in the `start` state. But the [fog of war](https://en.wikipedia.org/wiki/Fog_of_war) means that uncertainty soon arises: we don't know how the dice will land, so we don't know the outcome of the very first battle. Subsequent battles add more uncertainty. \n", "\n", - "The function `campaign_probdist` calls the function `battle_update_probdist` to update the probability distribution to account for one battle, in all the possible ways it can turn out. The key line in `battle_update_probdist` is\n", + "`campaign_probdist` calls `battle_update_probdist` to update the probability distribution to account for one battle, in all the possible ways it can turn out. The key line in `battle_update_probdist` is\n", "\n", " outcomes[update(state, dead)] += probdist[state] * dead_probdist[dead]\n", " \n", @@ -795,6 +798,7 @@ " plt.figure(figsize=(10, 5)); plt.grid()\n", " plt.title('Each line: attackers with Δ more armies than defenders')\n", " plt.xlabel('Number of Defenders'); plt.ylabel('Win Probability for Attackers')\n", + " plt.yticks([i / 10 for i in range(11)]); plt.xticks(range(0, 61, 5))\n", " for delta in deltas:\n", " winprobs = [attacker_win_probability(campaign_probdist((max(0, d + delta), d))) \n", " for d in defenders]\n", @@ -809,7 +813,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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" ] @@ -828,7 +832,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Note that the purple line (fourth from bottom), where the number of attackers exactly equals the number of defenders, gives a low win probability for a small attacking force, but reaches 50% for 12-on-12, and 73% for 60-on-60. The red line, where the attackers have one more army than the defenders, dips from one to two defenders but is over 50% for a 6-on-5 attack. Similarly, the green line, where the attackers have a surplus of two armies, dips sharply from 75% to 66% as the number of defenders goes from 1 to 2, dips slightly more for 3 and 4 defenders, and then starts to rise. So overall, an attacker does not need a big advantage in armies as long as there are many armies on both sides. Even when the attacker is at a disadvantage in numbers (as in the bottom grey line where the attacker has five fewer armies), the attacker can still have an advantage in win probability; with 55 against 60 the win percentage is about 57%." + "Note that the purple line (fourth from bottom), where the number of attackers exactly equals the number of defenders, gives a low win probability for a small attacking force, but reaches 50% for 12-on-12, and 73% for 60-on-60. The red line, where the attackers have one more army than the defenders, dips from one to two defenders but is over 50% for a 6-on-5 attack. Similarly, the green line, where the attackers have a surplus of two armies, dips sharply from 75% to 66% as the number of defenders goes from 1 to 2, dips slightly more for 3 and 4 defenders, and then starts to rise. So overall, an attacker does not need a big advantage in armies as long as there are many armies on both sides. Even when the attacker is at a disadvantage in numbers (as in the bottom grey line where the attacker has five fewer armies), the attacker still has bettern than 50/50 odds with 45 attackers or more." ] }, { @@ -887,7 +891,7 @@ "assert battle_deaths_probdist((2, 2)) == ProbDist({(2, 0): 581, (1, 1): 420, (0, 2): 295})\n", "assert battle_deaths_probdist((3, 2)) == ProbDist({(2, 0): 2275, (1, 1): 2611, (0, 2): 2890})\n", "\n", - "assert set(rolls(2)) == {(1, 1), (1, 2), (1, 3), (1, 4), (1, 5), (1, 6), \n", + "assert set(all_rolls(2)) == {(1, 1), (1, 2), (1, 3), (1, 4), (1, 5), (1, 6), \n", " (2, 1), (2, 2), (2, 3), (2, 4), (2, 5), (2, 6), \n", " (3, 1), (3, 2), (3, 3), (3, 4), (3, 5), (3, 6), \n", " (4, 1), (4, 2), (4, 3), (4, 4), (4, 5), (4, 6), \n",