Thomas Grip of Frictional Games, the creators of Amnesia and Soma, tries to get to the mechanical bottom of “Walking Simulators”. Comparing their core mechanism to other kinds of games centered around moving an avatar around, he concludes that it is probably not the walking itself that keeps players engaged. Instead those titles seem to require a certain “meditative state”. He is not content with assuming players will be wanting to reach that state of mind though. Instead he hints at new possibilities to densely pack the environment with important information, which Frictional seems to be aiming to explore in future games.
Walking forward is just a matter of pressing down a key or stick. And unless you are my dad playing a game, this doesn’t pose any sort of challenge at all. Your brain is basically unoccupied and the chance of your mind starting to drift is very high. Instead of being immersed in the game’s world you might start thinking of what to cook for dinner or something else that is totally unrelated to the experience the game wants you to have.
Recently some single-player strategy games, such as Auro: A Monster-Bumping Adventure or Minos Strategos, started using ranking systems of dynamic difficulty, specifically to combat some of the long-standing problems of the highscore model. In his new article, Ethan Hoeppner argues that this approach, while being a step in the right direction, comes with its own problems and can be improved upon further. He suggests presenting players with optional challenges, and discusses a difficulty format based on a single “par” number in depth.
Keith Burgun’s new piece contrasts the meaning of solvability in the computational sense with how it can be defined to be useful for game designers. On top of that it makes a few unusual points about how “too much depth” and in turn “too little sovability” can actually lead to the opposite of keeping the game interesting for its players in the long run.
Ethan Hoeppner builds off of his definition of “information generalizability” and especially the difference between calculation (the “hard” mathematical solution to finding the best possible move) and analysis (the more intuitive and automatic process of making ambiguious decisions). Interestingly he also draws a connection to the “burden of optimal play”:
The fun strategy and the strategically optimal strategy should be one and the same, but if you give the player infinite time to calculate, they aren’t. You force the player to choose which strategy they will go with: the fun strategy of using analysis, or the boring-but-optimal strategy of using calculation.
On his blog Wonderlust, Elliot George recently wrote about emergence and chaos in games. Continuing his previous explorations of systemic learning, he delved deep into the nature of complex emergent behaviors and their often ambiguous implications in regards to game design:
So there is a kind of tension here, chaos is good for increasing the number of mental models that we use, and therefore offers a lot of opportunities for systemic learning, but it also increases the usefulness of memorisation, which is mostly surface learning.
Brett Lowey recently put together a whole collection of posts laying out the game design guidelines behind the BrainGoodGames releases. The ten “design commandments” contain many state-of-the-art design principles of deep and original strategy games.
But beyond “classics” such as elegance, emergence and ambiguity, there is also a strong focus on the experience of playing. Putting fun and constant intellectual enrichment first, as well as treating the player’s time as a valuable good, are core pillars of the described design philosophy.
Keith Burgun explores the topic of “strategy vs. tactics” from a new perspective. The concept of “strategic arcs” serves as a tool to provide strategy games with a more coherent structure. A careful distribution of those arcs can not just help in determining the optimal length of a game, but also in creating “more unique and special” games overall.