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Puzzle Design in Last Train to Timbuktu: Challenge Modes
by Scott MacLean on 03/23/13 02:08:00 pm   Featured Blogs

The following blog post, unless otherwise noted, was written by a member of Gamasutraís community.
The thoughts and opinions expressed are those of the writer and not Gamasutra or its parent company.


This is the second post in my series about puzzle design in Last Train to Timbuktu. If you read the first post, you'll recall that it's actually about designing a puzzle designer, since the game's puzzles are all randomly generated. If you haven't read the first post, you should. If you really don't want to, let me quickly say that Last Train to Timbuktu is a puzzle game in which you rotate rows and columns of tiles to create a path of train tracks between stations.

In part 1, I described how the game generates puzzles by randomly wandering around the board laying down train tracks, and then shuffles them up by rotating rows and colums of tiles - the same movements players use to solve them. These straightforward single-path puzzles are used for the race mode of Last Train to Timbuktu.

A race puzzle. A race puzzle.

Today I'm going to look at how the puzzle designer creates more elaborate puzzles for the game's challenge modes. This was, for me, one of the more interesting aspects of designing Last Train to Timbuktu, and (naturally) not everything worked out quite as intended, so this post is also somewhat of a postmortem.

Why add complexity?

Most readers here are probably familiar with Sid Meier's famous assertion that "games are a series of interesting choices." There are obviously orders of magnitude difference in complexity between a game like Civilization and Last Train to Timbuktu, but I think this maxim is still applicable as something to strive for.

Choosing which moves to make to solve a single-path puzzle is interesting and satisfying. But these choices are made in a context with a single goal -- connect the train stations -- and a single way to achieve it -- make the train tracks follow the single path. I felt that adding complexity to the game's goal structure would create interesting higher-level "strategic" decisions. Based on the player's high-level choices, their move selections become interesting low-level "tactical" decisions.

That's the theory, anyway! Let's see how it worked in practice.

The Challenge modes

Before discussing the specific ways in which the puzzle designer adds goal complexity, I should briefly give some context by describing the game's challenge modes. There are two: a "time challenge", which gives the player five minutes to solve as many puzzles as they can, and a "move challenge", which gives them sixty moves to solve as many puzzles as they can.

Challenge mode available!

The goal in each mode is to get as many points as possible. Each puzzle the player solves earns them points based on the length of the path the train took (longer paths give more points), and how scrambled the puzzle was initially. The train departs as soon as the stations are connected, and takes the longest available path between the stations.

Puzzle elaboration

When creating a puzzle in one of the challenge modes, the puzzle designer always starts by creating a single-path puzzle. It then might apply one or more of three puzzle variations, which I will discuss in more detail.

  1. Creating additional paths
  2. Adding power-up stations
  3. Adding bonus flowers

Additional paths

If the puzzle's single path is long enough, the puzzle designer randomly chooses whether or not to introduce additional paths between the stations. If it chooses to, it picks starting and ending points on the existing path, and lays down new train tracks between those tiles. This process causes the stations to be connected by at least two different paths.

A puzzle with multiple paths. A puzzle with multiple paths.

Because the scoring system favours long paths, and long paths typically require more moves to create, there is a trade-off between getting a higher score and spending more of a limited resource (time/moves). Adding more paths between the stations opens up more ways to solve the puzzle. The player can balance the puzzle's difficulty against their remaining resources and choose to go for a long path, or to solve the puzzle as quickly as possible, but earn fewer points.

Power-up stations

Every so often, the puzzle designer repeats the path creation process I described last time and adds a second pair of "power-up" stations to a puzzle, along with a path connecting them. If the second pair of stations is connected when the player solves the puzzle, they get extra time or moves, extending the game.

Power-up stations Power-up stations

Like the first variation, adding the second path usually creates multiple paths between the original stations, and players can choose which path they will build. But in addition, it introduces an optional goal, which the player can either take or leave. The power-up stations offer the possibility of more points in the future in return for more time and moves now, and the player must decide whether the investment is worthwhile.

Bonus flowers

Sometimes, especially with larger puzzles, the single path between stations leaves many tiles empty. I used this as an opportunity to introduce more optional goals. The puzzle designer randomly places bonus flowers on empty tiles before scrambling the puzzle. Flowers come in three colours: red, white, and blue. If a flower is on a tile of the matching colour when the player solves the puzzle, it earns them some extra points. Similarly to the power-up stations, the player must decide whether to use valuable time and moves for "flower arrangement". In this case, the payoff is immediate, but significantly smaller than the largest possible deferred payoff from power-up stations.

Bonus flowers Bonus flowers


As you can see, my efforts to introduce more complexity into the player's decisions center on two general ideas:

  1. optional goals with either deferred or immediate payback for immediate investment, and
  2. multiple, non-equivalent puzzle solutions at different risk/reward points.

I think these are both useful tools for creating interesting decisions. The question is, how well did they work in the specific case of Last Train to Timbuktu?

The power-up stations and bonus flowers seemed to be fairly effective. Players tend to try to get them, unless they decide it's not worth it due to difficulty or lack of resources. This line of thinking isn't quite as "strategic" as I would have liked, though. Players typically don't worry much about running out of time or moves until they've almost run out. That's when the decisions become most interesting.

Multiple paths on their own had mixed success. At most difficulty levels, the puzzles are just not scrambled up enough path-selection decision to be interesting. It's often just as easy to get a long path between stations as it is to get a short one. However, on the harder difficulty levels, the situation is different. The puzzles are typically larger and significantly more scrambled than on easier levels, so it's much more common for one path to be easily solvable (but short) and another to be very difficult (but worth many many points).

Finally, the blue stations and flowers have another effect which I haven't touched on yet: they spread out the range of scores possible at each difficulty level. By earning bonus points and additional resources, players can achieve higher scores at a given difficulty setting than would otherwise be possible. This (hopefully) gives them a feeling of increasing mastery as they get more efficient at arranging flowers and solving multiple paths. Hopefully it also contributes to a feeling of the difficulty gap between levels. When the player bumps up the difficulty, they generally become less efficient, and may not be able to reach as many power-up station puzzles as before, setting the stage for a new phase of increasing mastery.

I hope you've enjoyed this discussion of the design choices and motivations underlying Last Train to Timbuktu's puzzle designer! Next time, I'll conclude the series with a look at difficulty levels and how they impact puzzle creation.

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