Temposchlucker

BK said: It is not at all clear that it is easier to improve by a fixed percentage on harder problems than it is on easier ones. Back in the days of the Bain Experiment, I found that reducing my solution times by a fixed percentage for my first pass through the first batch of problems gave a good fit to my solution times on the first passes through the later batches of problems. That appears to be roughly right for Woolum too. I advocate to train every specific task that you have to perform in a specialized way. Optimized for that specific task. Preventing diminishing returns. The first thing to do is to determine which tasks we are talking about. Every tasks has its own specialized sets of patterns associated with it, and if you don't find out which patterns to learn, chances are high that you don't learn these patterns at all. First task: 20 tactical elements. The first task we have identified is that we have 20 - 30 elementary tactical themes, depending on t

. . . . In order to enhance the speed of solving tactical problems as much as possible, I work with high rated (2300 - 2400 std rating) problems. These often take me half an hour to an hour to solve. If I can speed that up to under 3 minutes, I'm 10-20 x faster. With easy problems it is much more difficult to speed up the same percentage. 3 minutes is the average time you have per move in a long OTB game. Another advantage is that when you need an hour to solve a problem, you can use a stopwatch and a logbook to write down what it is what you are actually doing and what exact costs so much time. My search algorithm is actually developed for duplo attacks and not for traps. And it shows. Whenever I have to chase the king, I'm starting to consume time and to make errors. (I consider a mate to be a special instance of a trap.) This means I will have to work out a separate search algorithm for chasing the king. I will make a set of high rated mates with >4

In my quest to define an intelligent search algorithm for positional chess I had to swallow another disappointment. I bought the book Chess Blueprints: Planning in the Middlegame of Nikolay Yakovlev. I intended to make flashcards of the 188 blueprints he provided. Until I discovered that the author didn't computercheck his book. What's the use of learning the blueprint of a positionally won game when in reality you are loosing the exchange in that particular position. I didn't expect that anno 2010 (the date of publishing). So once again I will have to think for myself. Let's see if we can find a natural hierarchy for chess moves. What do you think about this: Tactics. Targets. Invasion points. Open lines. Space. Tactics. In the end, you will win a game by executing a tactic. If there is a tactical combination around, it usually has the highest priority. Fisher said: Tactics flow from a positionally superior game . How does that work? How does one

. . . . . . . Since my new approach to study tactics my FIDE estimated ATH increased from 1798 to 1844. The graph above gives you a clue how to interpret these figures. 46 points in one week, not too shabby! My new approach doesn't cover long king chases very well.  I'm very bad at it either. Maybe I must find an apart search algorithm for that.

Cure tactical flaw. In the previous post I found a major flaw in my approach to tactics and I belief I have found the way to cure it at the same time. The flaw is that I act as a headless chicken when investigating a tactic. The cure is to look in a systematic way. I expect that it will take a few months to cure. Preventing radio silence. Since I don't want to have a radio silence during these months, I will think out loud about the ensuing step. Can we deploy this method to positional chess too? I see no reason why not. Today I read all my posts I have written sofar about positional play (quite a lot!). What is the goal? The first problem we have to solve is to find out the core of the matter. My breakthrough in the previous post came about when I realized that I must be on the lookout for one of the six methods to gain wood. Without one, there can be no gain of wood hence no tactic. Can we find an analogy in positional play? In my blogposts I found no less than six d

The move order problem. In the previous post and its comments we saw what the core problem is when calculating. We recognize all kinds of patterns, but we have trouble to find the right move order due to the vast amount of possibilities. It takes too much time to investigate all possibilities. Brute force. Munich proposes to solve this problem by brute force. This means that he still wants to investigate all posibilities by trial and error, but tries to speed up the process by learning all kinds of patterns by heart. Search strategy. What I propose here is to add intelligence. Can't we find an intelligent strategy here that outperforms the brute force method? I have tried the brute force method myself for years and walked into the law of diminishing returns. If we are able to prune branches we can speed up the process by not calculating some lines. In stead of running around like a headless chicken (which is my usual state when in trial and error mode). Of course I can&

Let's have a closer look how the basic elements add up to the total combination. That might give us more insight what the effect is of training of the basic elements only and if that is sufficient to see the whole combination. Let's take the following 1900 rated problem. . . . . White to move. See the solution here . I recognize the following targets: king and rook Attacker: Queen Attacking square:d5 . . . . The attacking square d5 is defended by 3 pieces: . . . . Which leads to the following question: can I remove those 3 defenders with preservation of tempo? I can threathen and take the bishop with tempo via Ne5, Nxc4. . . . . I can get rid of the black queen and the knight by sac'ing the exchange with Rxe7 . . . . Which adds up to the complete combination: 1.Ne5 Qf8 2.Nxc4 bxc4 3.Rxe7 Qxe7 4.Qd5+ wins the rook. As always perfect fitting in m

. . . . At the previous post I made the following comment: This means that the transfer ratio is reciprocal to the complexity of the pattern. In order to maximize transfer we must minimize complexity. I doubt that. The reason that I have doubts is that I don't have proof that it actually works. It hasn't always been that way. Especially my experience with Troyis once seemed to indicate that it might work . The idea is very elegant and tempting, of course. Learn to do the skills and pattern recognition you need almost every move and do it as fast as possible. With this idea in mind I have spent 1000 hours or more with the following exercises: Low level drills of DLM. Exercices of CD Maurice Ashley teaches chess. 3 board vision exercises by Fritz. Knightmoves by playing Troyis. Tons of low level tactics. Tragically these exercises didn't have a measurable effect. The main problem is the relevance of the skill in relation to the outcome

. . . . In a previous post I said that pattern recognition is the only way to transfer a solution from one problem to another. Maybe there is a second method: skill. A skill is problem independent. The skill to see wether a piece is attacked for instance. If I improve this skill, it will have an effect on all positions, not just on the positions I used to train that skill. To make matters more complicated, a skill can depend to a certain degree on the ability to recognize patterns or work in combination with it. Aox said: Saariluoma conducted a series of simple experiments which suggest that grandmasters are much quicker than novices in certain lower-level perceptual proc or esses. In the first of these experiments, a king of one colour was placed on the chessboard, along with a piece of the other colour. The subject had to state whether the king was in check or not. The average latencies were as follows: novices: 1550 ms, class players: 1250 ms, exper

. . . . Green = target Orange = attacker Bright yellow = focal point 1st order (route from attacker to target). Dark yellow = focal point 2nd order (route from attacker to target). Blue = piece that causes the weakness of the bright yellow squares. The topology of the board, which square is weak and which is strong, is caused by the the position of the pieces. So there is a certain relation between the patterns of the pieces and the patterns of the weak squares that are derived from it. White can outnumber black on the bright yellow squares within two moves. The pieces on the blue squares prevent black from defending these squares within the same amount of tempos. Bf8 is not only standing in the way, it is bound to the defense h6 for at least one tempo, so it is immobile too. I read somewhere in a scientific paper that the eyes of a gm rest more often on an empty square during calculation than on a piece. With conscious thinking, you can calculate whi

In real wars the topology of the landscape has important tactical implications. If you manage to conquer a hill you have an advantage. The same is true for chess. If you manage to conquer an outpost for your knight, it gives you an advantage. The problem with chess is that the topology of the terrain isn't directly visible. Take for instance the following problem: . . . . White to move. You can find the solution here . By solely trusting on the recognition of the constellation of the pieces, it is clear that you must have stored an awfull lot of constellations before you will be able to solve this one fast. But if we manage to develop our ability to see the hidden topology of the terrain, things might become much easier. The focal points of the position above are g7 and g8. Why? What are the characteristics of these squares? The squares are in contact with a target (the king). What does in contact mean? That depends on the attacker. If I place a queen

Transfer of the solution from one problem to several other similar problems is based on the mental ability to recognize lookalikes. It cannot be otherwise. All the methods of transfer I mentioned in the previous post share this mental ability as underlying principle. The mental ability to recognize lookalikes = pattern recognition. So all transfer must in essence be based on pattern recognition. The only thing that differs between the several methods of transfer is the type of pattern. A pattern can be geometrical or textual or conceptual for instance. Only the ability to find lookalikes can multiply the solution from one problem to another. I have analyzed the questions I ask myself during the phase of "adding intelligence". I can divide them in two: questions that relate to the geometrical patterns of the squares and questions that relate to the thoughtprocess during solution. As you might remember I distinguished between two moments when to add intelligence: During