Note: This post deals with content discussed in the first interview with Raymond Chandler.
Ray offered insight into the design behind board games with his expertise. This isn’t the same type of expertise we intend to model with the board game recommendation engine (we’re not building an engine that creates board games, just one that recommends them for play), but in some respects, it’s still relevant to our problem domain. (It’s also important to note that Ray is an a zealous board game player, and so he is still a highly useful expert.)
The interview writeup goes into greater detail on his explanations of board game design, but he gave some good possible game attributes and other input that we hadn’t considered, such as the “ramp” and “tempo” of a game, and the average player skill of those in the group. We discussed the possibility of a ”similar games engine” to add variety to search results with Ray. Ray didn’t like the idea of directly linking games, as it was demanding on experts and poorly scalable. He recommended as an alternative that we link attributes across games so that newly added games would be immediately integrated in the system.
While what he recommended made sense, the notion of linking arbitrary attributes is rather complex. An example of his proposal is to link dice-rolling to card-playing systems as similar. When a new card-playing game is added, no new links will need to be established; the engine will know that the games are similar because of this link. If all we’re to do is link gameplay mechanics, then that is a reasonable approach. However, it may be more effective to link arbitrary game attributes in some manner, such as linking dice rolling mechanics to luck-based gameplay (in the luck vs. skill attribute). The problem is that linking attributes is such a manner is rather complex, especially when the only reason we began down this road was to add variety to recommendations; a nice feature, but an unnecessary one.
I think this thought shouldn’t be accepted or rejected so quickly. It will require discussion with the team at the next meeting, and potentially further exploring this option in the next interview with Ray.