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In a previous article on ChessBase, I introduced a new chess variant called Switch-Side Chain-Chess (SSCC) that increases the complexity of chess significantly without, in principle, affecting the size of its game tree (this is an idea that is not very easy for some people to grasp, by the way). It achieves this by the simple addition of a rule that allows either player to switch sides with the opponent if a ‘chain’ or connected sequence of pieces occurs on the board. Imagine getting up and changing seats with your opponent every now and then – naturally, under time controls, you should also obtain the time of your opponent in exchange for yours. None of this affects the number of possible positions on the board but changes the dynamics of the game for the players significantly.
Two-time Arimaa World Champion Fritz Junke was probably correct when he said that SSCC would be difficult for humans, as opposed to computers, to wrap their minds around. If precise logic and calculation are sufficient to play at the highest levels – as it is with regular chess – this difficulty becomes clear because being thrown into your opponent’s shoes at any point is easier for a machine to handle. Give it a position (any position) and it just calculates from that point on like nothing happened prior. However, introduce the concept of chains and humans probably have the advantage. This is because regardless of how well the computer plays, the formation of a chain on the board can change things instantly. There is also presently no known algorithm that detects SSCC chains infallibly. In fairness, humans might tend to miss a few as well.
Fritz Juhnke is the 2005 and 2008 Arimaa World Champion. In 2009 he published the book Beginning Arimaa: Chess Reborn Beyond Computer Comprehension. He is currently a Ph.D. student in applied mathematics at Southern Methodist University. His article on Computer-resistant chess variants appeared in 2014. Arimaa is a modern abstract strategy game that is playable with chess equipment. It was published in 2002 by Omar Syed, an Indian American computer engineer trained in artificial intelligence. Syed was inspired by Garry Kasparov's defeat at the hands of the chess computer Deep Blue to design a new game which could be played with a standard chess set, would be difficult for computers to play well, but would have rules simple enough for his then four-year-old son Aamir to understand. |
Then we come to the difficult part, i.e. in deciding whether or not to switch sides if a chain is formed. It is not always a simple matter of seeing which side is better at the moment given say, a regular chess engine’s analysis of the position. One also needs to factor in the likelihood of specific chain formations in the future (which is extremely difficult for computers to do). This may be analogous to predicting weather patterns on the board. So even a weak chess player could actually have a reasonable chance at defeating a very strong SSCC engine that plays the regular chess part well but is not so good at detecting chains and even less so in deciding whether or not to switch. This is to say nothing of preventing the opponent from forming chains on the board in the first place whilst trying not to lose at the regular chess component of the game. A club player may even be able to defeat Carlsen at this variant.
In any case, SSCC is a lot of fun, at least in my experience, once people get the hang of it. In my previous article, a link to a rudimentary computer program that plays SSCC was also included. It was developed under my supervision by my research assistant under a previous research project but some bugs were discovered later. Unfortunately, he has disappeared back into the Middle-East and taken the code with him so there is no chance of fixing them. The project investigated the possibility of creating a game that is theoretically and perceptually more complex for humans than chess without increasing the size of the game tree which would be an additional burden for computers, as is the case with Go and Arimaa, for example. So such a game would not require more processing power due to the larger number of possible game positions but rather cleverer artificial intelligence (AI) to play well, which is a topic for another project.
One can still play a reasonable game with the occasionally buggy software (but avoid queen-side castling, for instance) to get a feel for it. Of course, playing against a real person is always more enjoyable. The program asks for confirmation before switching because the chain detection is not perfect; although the rules of SSCC do not require permission of the opponent. It has virtually no sense of whether or not to switch sides apart from a simple inversion of the positional evaluation score when a chain is detected. Further work is definitely required in this area.
Below are a couple of games I played in real time against the SSCC program so readers can get a sense of how tumultuous things can get. There is no commentary (the videos are silent) so readers may try to guess at which points focus shifted from the regular chess playing to switching sides, and back. Suffice to say I knew I could almost never defeat the computer at the regular chess component so I had to use my human intuition with regard to chain formation in order to win.
My YouTube channel actually features mostly computer generated chess problems or constructs (that can also be used by players of all levels, including school children, to train) but occasionally I upload other stuff as well, such as these. Please subscribe, ‘like’, comment and share if you are so inclined.
I have also received feedback from some readers about SSCC, sharing ideas about various ‘theories’ behind effective play. For instance, one only need look for a forced sequence of chain formations to win but it turns out that such a sequence is not very common or as easy to see as it might first seem, to say nothing of the opponent seeing it first and playing to prevent it or taking the reasonably good chance that it would go unnoticed and capitalizing on that somehow. One reader used the example of Game 3 in the recent 2014 world championship match between Anand and Carlsen. Had it been an SSCC game, Carlsen would have won (had he seen the proper continuation).
[Event "Carlsen-Anand World Championship"] [Site "Sochi RUS"] [Date "2014.11.11"] [Round "3"] [White "Viswanathan Anand"] [Black "Magnus Carlsen"] [Result "1-0"] [ECO "D37"] [Annotator "admin"] [PlyCount "67"] [EventDate "2014.11.07"] 1. d4 Nf6 2. c4 e6 3. Nf3 d5 4. Nc3 Be7 5. Bf4 O-O 6. e3 Nbd7 7. c5 c6 8. Bd3 b6 9. b4 a5 10. a3 Ba6 11. Bxa6 Rxa6 12. b5 cxb5 13. c6 Qc8 14. c7 b4 15. Nb5 a4 16. Rc1 Ne4 17. Ng5 Ndf6 {[#]} 18. Nxe4 ({In Switch-Side Chain-Chess Carlsen could have chosen to switch sides with Anand and continue switching at each move as follows:} 18. Rc4 Qd7 19. f3 Rd8 20. Qd3 Ra5 21. Ke2 Qxb5 22. g3 Qxc4 23. g4 Qc3 24. Qd2 Qxd2+ {After this, Carlsen stops the switching and lets Anand continue with the inevitable 25. Kf1 Qf2#, and Carlsen wins with Black.} 25. Kf1 Qf2#) {The game continued} 18... Nxe4 19. f3 Ra5 20. fxe4 Rxb5 21. Qxa4 Ra5 22. Qc6 bxa3 23. exd5 Rxd5 24. Qxb6 Qd7 25. O-O Rc8 26. Rc6 g5 27. Bg3 Bb4 28. Ra1 Ba5 29. Qa6 Bxc7 30. Qc4 e5 31. Bxe5 Rxe5 32. dxe5 Qe7 33. e6 Kf8 34. Rc1 1-0
So the curious thing is, would Carlsen, in a SSCC game, have seen this forced sequence? Even better, could Anand have foreseen it even earlier and played to prevent it? Mind-bending indeed; but then again, so is the universe we live in. From an AI standpoint, the heuristics needed to play this variant well would therefore be quite unlike anything developed before, and perhaps lead to advancements in other areas just as computer chess has contributed to molecular computing, automated theorem proving, computer music composition, machine reading, cognitive development, treatment of psychiatric illness and child education, to name a few. This is largely why we researchers in AI and game intelligence today do what we do, while still having fun.
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Dr. Mohammed Azlan Bin Mohamed Iqbal received the BSc and MSc degrees in computer science from Universiti Putra Malaysia (2000 and 2001, respectively) and the Ph.D. degree in computer science (artificial intelligence) from the University of Malaya in 2009. He has been with the College of Information Technology, Universiti Tenaga Nasional since 2002, where he is senior lecturer (class A). Azlan is a member of the ICGA, IEEE, AAAI, AAAS and chief editor of the electronic Journal of Computer Science and Information Technology (eJCSIT). His research interests include computational aesthetics and computational creativity in games. Azlan Iqbal Web site. Additional links: Facebook, Twitter, Google Plus, Youtube. |
2/6/2015 – Computer generated chess problems for everyone
Now they are composing problems that fulfil basic aesthetic criteria! Chesthetica, a program written by Azlan Iqbal, is churning out mate in three constructs by the hundreds, and the author is posting them in a very pleasing format on Youtube. How long will Chesthetica theoretically be able to generate new three-movers? Quite possibly for tens of thousands of years.
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.