2013/14 start has been again focussed on existing product infrastructure
enhancements. During the months August to September we were in tough competition
to maintain the position of our Spades Free, from two strong rivals. At one
point we were a poor third. However a concerted push to improve the product
saw us return to the #1 slot and now the latest release will add 4 new game
variants, including the use of jokers, so we expect to please many more new
A diversion in October was a trip to AIIDE in Boston and North Eastern University, where we presented a talk on the collaborative work between York University and AI Factory on delivering information set Monte Carlo tree search for our Spades program above. This is an intuitively hard to grasp mechanism for tree-searching imperfect information games, but this method, combined with AI Factory heuristics, has managed to deliver a consistent level of quality play.
In the meantime our Chess Free has persistently strengthened and is by far our most popular product. Over the Xmas season we made it stronger and in the recent new release we added a much requested feature, a tutorial. This has implemented a different take on the usual idea and rather than divert the user into a separate tutorial, which can feel a bit like an exam, we have provided in-play help. Such a system might more often manifest as simply an offer of a selection of moves to play, from which the user has to choose. This type of multiple choice style encourages the user to avoid thinking altogether and instead just pick one of the offered options. Our approach has been to simply recommend a piece to move, but not where to move it to. This obliges the user to think about what that move should be. Of course for many moves the choice of move for one piece may well offer only one reasonable option, but many times the piece recommended might appear to be the wrong piece to play, neglecting some other defence or capture offered. In this case the recommendation becomes a puzzle set as the selected piece must have some non-obvious beneficial play that is better than the more obvious choice. These become natural in-game problems for the player to solve.
This is also a great system for beginners as it gives an indication of which pieces they should be developing so guides them to find plausible plans. For the more experienced player the tutor nudges them from making simple mistakes while still giving them the option to follow their own plan. They can therefore avoid the unsatisfactory and annoying need to have to take back and replay to cancel blunders. The user can keep this blunder avoidance without spoiler suggested good pieces to play by setting the tutor at the lowest level. Finally players wanting to take on levels they otherwise cannot beat can have the tutor lift them to a higher level without having spoiler explicit moves offered.
Players still stuck can take a full hint and, those needing the highest quality suggestion, can use the newly added analyse option.
As indicated in the newsletter header, we have started down the path of localisation for our products. Currently only Chess and Move it! are translated but others will eventually follow. An important drive for this was to have Russian Cyrillic covered for Chess, given that we had so many players in Russia.
The other big new thing is Google Play Games. It would be hard to imagine that this might not be very important for the future of gaming on Android, and so we fully intend to support it. We currently only have Solitaire and Four in a line supported, but others will quickly follow.