Dream Pod 9's Silhouette System part 2

When we last left our intrepid system, I had graphed probabilities of success at various difficulty thresholds for different skill levels, holding attributes constant, and I made the claim that the system encourages min-maxing.  Let us follow up on that.

This table shows the probabilities of succeeding at tasks with a difficulty threshold of 6, which is hard, for various combinations of skill and attribute.  It also shows the character creation point cost of each skill/attribute combination, and the point cost per percentage change of success.

We see that costs mirror each other across the center diagonal, and it is a more efficient use of points to buy a high attribute than a high skill.  Even more important to note is that Attributes are applicable to many skills, and are sometimes used to determine secondary traits (Health is the average of Fitness, Psyche, and Willpower).  So, not only would it be more efficient to buy a high attribute for just one skill, there is compound efficiency for buying a high attribute in general and with multiple related skills.

This table shows the average probabilities of success across tasks with difficulty thresholds from 1 to 7.  That should be a relatively standard distribution, since a threshold of 4 is considered average.

A notable difference here is that it is actually more efficient in some cases to buy a lower attribute than skill, but only when the average probability of success is less than 51%, which is not usually desirable in a heroic simulation.  At the useful levels of success, it is still more efficient to buy a high attribute, even for a single related skill.  We also see that an attribute of 2 and a skill of 3 is a kind of sweet spot for good success at a moderate price.

There are many available skills, but the overwhelming majority of them are based on just three attributes: Agility, Knowledge, and Creativity.  As far as skills go, this means there is a strong incentive to min-max, and just pick one of the three areas to focus on while taking negative scores in the other two.  If you don't care about having a lot of skills, and want more of a brute character, scrap all three and raise the Build, Fitness, Psyche, and Willpower attributes instead.

Since those three attributes apply to so many skills, it would be more appropriate to make a new version of each of the above tables for each number of desired skills, adding in only the average attribute cost per skill.  I am not currently inclined to make a dozen more tables.  This would make it drastically more evident that a high attribute score (a 4 is possible for a starting heroic character, but a 3 is practically as high as even a min-maxer should go) allows for the most success at multiple skills for an efficient price.

Something that I did not highlight is the fact that the same point pool is not used to buy attributes and skills.  It is impossible to use a huge number of points on attributes and then buy a bunch of low level skills as it is in GURPS.  This system guarantees a set block of points for skills.  If you don't want a lot of skills, use your attribute points to build a brute, and buy high levels of the couple skills you do want.  If you want a lot of skills, pick one of the three polyskill attributes to focus on, crank it up and buy many low level related skills.  I am glad that Dream Pod 9 split the pools this way, as it does slightly limit min-maxing and forces characters to have skills, but the system still does encourage attribute min-maxing within its point pool.

Also interesting is that it is incredibly difficult to increase attributes during play.  The experience point costs are  different than the character creation point costs, and strongly incentivize buying skills during play instead of saving up to increase an attribute.

RPG Mechanics Taxonomy: Probability Scales

It's taking me longer than I wanted to finish some analyses of Dream Pod 9's Silhouette system, so part 2 will be delayed while I tell you a bit about role-playing game mechanics taxonomy.

Humans love to find patterns and name things.  Our brains do it automatically, giving us ways to predict the outcomes of novel situations by comparing features to those of situations we have been in in the past, though not always accurately, often resulting in bad stereotypes and superstitious beliefs.  When we are mindful, we can harness this wonderful ability to organize information to facilitate analyses, searches, and predictions.  We give names to groups of items that share patterns of features.

Dr. Wayne Saunders of the Museum of Man developed a taxonomy of games that identifies 20 types of game based on how they are played, and three categories of games based on victory criteria.  He classifies role-playing games as "production" games because the goal is to create something rather than to win.  Within RPGs, I further break down games into categories based on patterns in their mechanics.

 In this post, I am going to focus on scales of probabilities that characters succeed at tasks they attempt as they relate to character creation or experience point costs.  There are other mechanics that I will address in later posts.  There are two main categories of probability scale features:  the method by which the scales are determined, and the patterns of increases in probabilities of success as they depend on point costs.  I will abbreviate these to Method and RoI (Return on Investment).

There are four Methods:

• Utility: The point costs of probabilities of success at tasks are intended to reflect how useful the tasks are in the game.  Tasks that occur frequently in the game would generally cost more points for a given success probability than for less common tasks.  In a typical RPG, Karate comes up a whole lot more often than Basketball, and would cost more points to be good at even though training in those skills may take similar effort in real life.
• Realism: The point costs of probabilities of success at tasks are intended to reflect how much effort it would take in the realm world to achieve such a success probability. Being an expert historian of spoons would cost the same points as being an expert computer programmer, even though one is clearly more useful (I won't tell you which one). 
• Constancy: The point costs of probabilities of success at tasks are all the same, regardless of task utility in-game or the effort required to learn how to accomplish the tasks in real life.  
• Arbitrary: The game creators just assigned costs to success probabilities without strictly or clearly using one of the other three methods.

There are four Returns on Investment:

• Increasing: The increase in probability of success increases with additional point expenditures.
• Decreasing: The increase in probability of success decreases with additional point expenditures.
• Equal: The increase in probability of success is the same for every point expenditure. 
• Inconsistent: The increase in probability of success is sometimes higher or lower or equal for successive point expenditures.

We may be able to place RPGs on a table based on their Methods and RoIs.

How would you classify your favorite system?

Dream Pod 9's Silhouette System part 1

I had a lot of fun playing Heavy Gear by Dream Pod 9 with friends back in undergrad.  DP9 came up with a game system it calls Silhouette.  I remember a friend telling me that it was mathematically optimized for 8-sided dice, but they just changed the dice to 6-siders because people tend to have d6s lying around.  Whether or not that is true, there is a little funkiness in the system.  Here is a brief intro to the dice system, and I will have a deeper report later.

In this system, characters have attributes and skills.  To perform a task, the player rolls a number of d6s equal to his character's skill level (if the skill is 0, 2 dice are rolled and the lower result is used), and the highest result is used, with any 6s over the first adding 1 to the result.  Then the appropriate attribute is added to the die result.  So, a player whose character has an attribute of 2 and a skill of 3 will roll 3d6, take the highest die result (+1 for each 6 over the first) and add 2.  The total is then compared to a difficulty threshold, and the character succeeds if the result is higher than the difficulty.  If the total equals the difficulty, there is a draw, which usually favors a defender, and I am counting as a failure.  If all 1s are rolled, there is a "fumble" and something bad happens regardless of modifiers.

Attribute scores effectively take away from a task's difficulty (or add to it if the attribute is negative, which is common; 0 is average for an attribute).  A difficulty of 4 is supposed to be average, 8 very difficult, and 10 or more practically unattainable.  Even the game creators describe the progression of success as "peculiar."

Just a cursory glance shows us that attempting tasks with a skill of 0 significantly risks fumbles, that there are diminishing returns as skills increase (I'll go more into that in part 2), and that you shouldn't count on rolling more than one 6.  Also, you can see how important attributes are, shifting the entire graph to the left or right.

We had a sniper in our party with a dexterity of 3, which is a very high attribute.  He was ridiculously successful at dexterity tasks for which he had little or no skill, such as piloting a Gear.  This system cries out for min-maxing, and game masters should be ready to impose limits and say the magic word: "no."