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Previously on ChessBase, I introduced the ‘digital synaptic neural substrate’ (DSNS) technology that is currently being used by my program, Chesthetica, to compose three-move constructs (a type of chess problem) by combining information from different domains, e.g. photographs and chess games. I also mentioned that I had planned to publish these problems or puzzles in a book. Unfortunately, the publishers I approached were hesitant and declined. This is understandable, as presumably books by even masters in the game are difficult enough to sell well these days.
Regardless, it turned out to be a blessing in disguise as it occurred to me that traditional methods of publishing are probably on the way out or not as important as they used to be. These days, thanks largely to computing technology, the individual is empowered enough to reach a global audience. Self-publishing (e.g. on Amazon Kindle) is a possibility, but then it occurred to me, why not publish the compositions of Chesthetica in a livelier format on YouTube for everyone and for free? I had set up my channel back in 2012 but never really found a practical use for it until now.
Readers may access the channel by simply searching for “Azlan Iqbal” on YouTube or following this link.
I upload new chess problems every day. The videos are accessible from the ‘videos’ or ‘playlists’ tab. The composition details of each chess problem are given in the description. Chesthetica handles the more creatively-demanding task of composing the problems and I merely put the videos together and upload them.
Each video plays with the initial position shown for about 30 seconds followed by the main solution. The more recent videos have some analysis included. Here is a clip of Chesthetica v9.47 at work, showing more detail than the clip from my previous article.
Minor updates to Chesthetica (presently in version 9.53) do not necessarily imply changes to the DSNS process itself. Most of the time they are cosmetic or routine functional enhancements to the program. For instance, starting with v9.50, Chesthetica uploads all its compositions created to a central FTP server where it is easier for me to collect. So I can have several instances of the program running on different machines (anywhere in the world, in fact) and can collect the compositions from them all more easily. Chesthetica also detects when I have collected them from the FTP and then uploads only the new ones.
White to play and mate in three: example of a computer generated chess problem
The chess problems I upload to my YouTube channel are actually from my personal collection of the compositions generated that I found interesting or educational at the time. I am still collecting these and will continue to upload them for all to enjoy. There are so many. These chess problems or constructs are not intended solely for the most aesthetically-desensitized master composers. I am neither trying to please or appease this group or compare what Chesthetica does to what they do. Some of Chesthetica’s compositions are simple yet educational. Most have some aesthetic merit that average and even some strong players can appreciate.
Chesthetica neither takes these constructs from actual games nor extrapolates them from endgame tablebases (which are currently limited to seven pieces, I believe). It is composing them by itself. It is not programmed or told what sort of compositions to create (beyond being of the #3 variety, at this point). There have been no detected repetitions of the compositions generated to date.
White to play and mate in three: a random Chesthetica-generated three-mover from the Youtube channel
One might ask where does Chesthetica “get its ideas”? I do not know. How or why should a computer be able to compose chess problems like these at all? Can computers autonomously do this sort of thing? These are also good questions and I believe the answer lies with the DSNS technology. Again, why it works is still an open question but clearly, it does work.
How long can this process of automatic composition continue? I am not sure. Given the size of the game tree and a conservative estimate of the subset of three-movers possible, quite possibly for tens of thousands of years to come. What new ideas might the compositions generated help us discover about the game and about the concept of creativity itself? These are among the questions I hope to explore in my continuing research work into computational creativity.
Once again White to play and mate in three – computer generated ideas
On that note, there has been some positive news with regard to my research grant application into applying the DSNS to protein folding (important in the search for cures to many diseases). An international research team has been assembled and the application has passed the first level of approval. There are three more levels to go and by the end, assuming it is successful, about 30-50% of the budget requested will likely be slashed (it is, by default, assumed that we are asking for more than we really need). Alas, this is the reality of scientific research today.
As for the publication related to the DSNS that I also mentioned in my previous article, it has been reviewed and revisions, as is often and should be the case in academic publishing, are required. So the publication itself is probably quite a few months away. In the meantime, I would hope that readers who are interested will take a look at my YouTube channel and the compositions generated. Maybe even have some fun trying to solve them. Please subscribe, comment and ‘like’ the videos, if you like. Feel free to share and embed the ones you find interesting in your own pages.
11/7/2014 – A machine that composes chess problems
Chess problems are an art – positions and solutions, pleasing to the mind and satisfying high aesthetic standards. Only humans can compose real chess problems; computers will never understand true beauty. Really? Dr Azlan Iqbal, an expert on automatic aesthetic evaluation, imbued his software with enough creativity to generate problems indefinitely. The results are quite startling.
7/26/2014 – Best ‘Chess Constructs’ by ChessBase readers
Chess constructs are basically an intermediate form of composition or chess problem, lying somewhere between brilliancies from chess history – and artistic chess problems, between real game sequences and traditional award-winning compositions. A month ago Dr Azlan Iqbal explained the concept asked our readers to submit compositions of their own. Here are the winners.
6/29/2014 – Azlan Iqbal: Introducing ‘Chess Constructs’
People love brilliancies from chess history – and artistic chess problems. But there is a big gap between the two. Positions from games demonstrate the natural beauty of actual play, while chess problems are highly technical, with little practical relevance. The author of this interesting article suggest an intermediate form, one you can try your hand at – and win a prize in the process.
9/2/2009 – Can computers be made to appreciate beauty?
Or at least to identify and retrieve positions that human beings consider beautiful? While computers may be able to play at top GM level, they are not able to tell a beautiful combination from a bland one. This has left a research gap which Dr Mohammed Azlan Mohamed Iqbal, working at Universiti Tenaga Nasional, Malaysia, has tried to close. Here's his delightfully interesting PhD thesis.
12/15/2012 – A computer program to identify beauty in problems and studies
Computers today can play chess at the grandmaster level, but cannot tell a beautiful combination from a bland one. In this research, which has been on-going for seven years, the authors of this remarkable article show that a computer can indeed be programmed to recognize and evaluate beauty or aesthetics, at least in three-move mate problems and more recently endgame studies. Fascinating.
2/2/2014 – A new, challenging chess variant
Ever since desktop computers can play at its highest levels and beat practically all humans, the interest of the Artificial Intelligence community in this game has been sagging. That concerns Dr Azlan Iqbal, a senior lecturer with a PhD in AI, who has created a variant of the game that is designed to rekindle the interest of computer scientists – and be enjoyable to humans as well: Switch-Side Chain-Chess.
