Devising a model of the game Part 1

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Devising a model of the game Part 1

by Jack May 7, 2015

Models can be very helpful in abstractly understanding systems. Many different fields use models to map behaviors of systems, organisms, relationships, growth and decay, procedures and so on and so forth. The need for a model for maze of monsters arose after a few playtests where it started to feel changes in the game were going around in circles.

With a model, I hoped to account for the rank, positions and stats of the different players, their different play styles, their relationships with one another, strategies and events that come up in the game.

At first I thought the easiest way to do this would be through an action/strategy tree. By listing all the possible actions a player might take, their objective for taking those actions, the overlying strategy behind those objectives and lastly the goal of the game, I could map out all the possible paths that a player might be able to take in the game. Different paths would close as the game progressed as certain paths became closed such as making an alliance with someone a player previously attacked or betrayed or finding gold if all the gold had already been collected.

This was the first result.

Strategy Tree

In maze of monsters, explorers juggle between two goals, surviving and getting gold. While the two goals do not directly conflict one another, concentrating on one tends to decrease the odds of successfully completing the other and both are necessary to win. I started simple by just focusing on the gold goal. I broke down this tree into 4 different levels. At the bottom is the goal, the ultimate task the players must accomplish that. The next level up which is comprised of different ways an explorer could get gold which also could be described as their strategy or how they go about trying to accomplish the goal. The following level up is what I refer to as the tactics. The tactics are short term groups of tasks that contribute to the overall strategy. The last tier or the top tier is not listed above (still in development) but is the final pool of all possible actions an explorer could take each turn. This pool is entirely drawn from the mechanics.

While this tree was effective at accounting for strategies and play styles, it had no information on standings of the players, player relationships and past events. Furthermore, this diagram itself became extremely clunky to use as I had to track players on a turn by turn basis to use this tree and I was looking more for a diagram where I could better understand how different entities introduced at different times in the game could affect the overall experience and player interactions. What would happen if the gold economy suddenly inflated in the middle of the game? How do player interactions progress as novice players fall behind or experienced players attack each other and burn alliance? What reaction would players have if I introduced some element that either pulled back the leading player or helped the lagging player catch up?

And so I moved onto another model. This model was more of a flow chart that would track player interactions with each other and record their different states as well as their overall environment. To track the progress of the game, I also had their positions match their physical positions in the game (around a table). This inspiration behind this model was a heavily abstracted view of the game where information from any turn in the game could be used to fill this abstract “snapshot” of the game to get an in depth view of what was happening in the game at that moment.

Initial State Chart

Players could all interact with one another while individual explorers (P#) each had special abilities which could affect the overall game state and economy. The Monster player also could affect the state of the game and the economy. The red lines tracked turn order. I started with the maximum number of players (4) as I felt it would be easier to remove players from the model than add them. Most of my playtests also had 4 players so it was easier for me to picture and build the models based on session reports I took.

While this model did give me some insight into player interactions and relationships, it lost the status and strategy that the tree diagram supported. Furthermore, having it rooted as a snapshot of the game as it progressed made this a very rigid diagram, at least mentally to me, so it did not adapt well to drastic dynamic changes in the game.



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